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IBM ILOG OPL IDE Tutorials

1. 55 Debug gg Hu Run Configurations Basic Configuration default M Fiter script amp 3 Scalable data Solution pool script 3 scalableWarehouse mod l solpoolscript mod tiii warehouse mod fiij warehouseCplexFitters mod warehouse dat The warehouse project Note that There are two models warehouse mod and scalableWarehouse mod used in different run configurations There is a warehouse dat file declaring external data for the warehouse mod model but there is no scalableWarehouse dat file There are four run configurations The first one associates the basic warehouse model and data The second one uses a variation of scalableWarehouse mod for you to learn the tuning tool See Using the performance tuning tool IBM ILOG OPL IDE TUTORIALS 15 16 B M The third one has been created specifically from scalableWarehouse mod for you to work with scalable data The fourth one uses another variation of scalableWarehouse mod for you to work with solution pools See Working with the solution pool The data The scalable warehouse model has no associated data file The numbers of warehouses and stores and the fixed cost are declared within the model file as shown below Data initialization in scalableWarehouse mod int Fixed 10 int NbWarehouses 50 int Nbstores 200 assert NbStores NbWarehouses 1 NbWarehouses 1 NbStores range Warehouses rang
2. What you are going to do Working from the example described in Presenting the transportation example you will set up the model and data see Setting up the transportation model and data run the model without a breakpoint and examine specific preprocessing scripts see Executing preprocessing scripts adda breakpoint and start debugging as explained in Debugging a preprocessing script that is examine the call stack monitor a loop by using a breakpoint to stop at each iteration step out of the execute function step into a function step out of the function monitor a function in a loop ILOG OPL IDE TUTORIALS The script variant of the example is supplied as file transp4 mod used in the run configuration named Even better sparsity which associates the model file transp4 mod and the data file transp4 dat of the transp project available at the following location lt OPL_dir gt examples op1 transp where lt OPL_dir gt is your installation directory IBM ILOG OPL IDE TUTORIALS 93 Setting up the transportation model and data 94 B M To start working with this example 1 Use the File gt New gt Example menu command to open the transp example The IDE displays the transp project in the OPL Projects Navigator Open the model file in the editing area 2 Double click transp4 mod to display this model in the editor 3 Scroll to the execute blocks There are three preproces
3. lt p bands e lt o GARY d FRA tuple supply string p string 0 lt p bands o GARY gt n lt p 400 700 800 800 1600 1800 200 300 tuple customer string p string d lt p bands d FRA gt lt p bands 300 300 100 75 650 225 250 500 750 a IloOplSettings object Object object Object undefined primitive constructor IloOplInputFile Variables view for call frame transp4 mod 66 transp4 For a large tuple set the values may not all be visible within the window In this case an ellipsis appears at the end of the cell Pass the cursor over the column to display all the values in a tooltip Click the Step Over values change ILOG OPL IDE or Step Into button TUTORIALS repeatedly to watch the value of the variables change in the call stack The variables are highlighted when their Problem browser Variables X 9e Breakpoints xt J Name Value or g prbands e lt o CLEV di STUS amp with a IloOplModel amp Cities GARY CLEV PITT FRA DET L amp 4 Products bands coils plate Capacity 625 tableRoutesType tuple tableRoutesType string p strin amp 9 TableRoutes lt p bands o GARY d FRA cost connection tuple connection string 0 string d route tuple route string p tuple e amp 4 Routes lt p bands e lt o GARY d FRA supply tuple
4. fi Problem browser 3 69 Variables Breakpoints xha Solution with objective 287 750 3 Name Value amp ee Data 6 E Gas lt 3000 70 10 1 2000 60 8 2 1000 50 6 1 gt f Gasolines Super Regular Diesel MaxProduction 14000 amp oi 5000 45 12 0 5 5000 35 6 2 5000 25 8 3 gt f Oils Crude1 Crude2 Crude3 ProdCost 4 amp Decision variables 2 Pa 0 750 0 E Blend 2088 9 2111 1 800 777 78 4222 2 0 133 33 3166 7 200 amp EY Constraints 5 ET ctCapacity sum g in Gasolines Blend o g lt Oil o capacity Ef ctDemand sum o in Oils Blend o g Gas g demand a g 10 ET ctLead sum o in Oils Oi o lead Gas g lead 1 Blend o g lt 0 ctMaxProd sum o in Oils g in Gasolines Blend o g lt 14000 ET ctOctane 0 lt sum o in Oils Oi o octane Gas g octane 1 Blend o g Property Value Problem Browser after execution oilSheet dat In the Problem Browser you can examine the model in the usual manner to see the contents of the various data structures in this example If you are not familiar with the Problem Browser see Understanding the Problem Browser in Getting Started with the IDE At the end of execution you see the following message in the Solutions tab IBM ILOG OPL IDE TUTORIALS 71 72 B M Solutions 3 Blend 2088 9 2111 1 800 777 78 4222 2 0 133 33 3166 7 200 a 0 750 0 Solution
5. 3 Double click Result in order to see the table s contents 60 IBM ILOG OPL IDE TUTORIALS The Result table after execution The table Result gives the results in rows for each crude gasoline combination It shows the blend as a number of barrels of each crude used for each type of gasoline and the amount spent on advertising that type of gasoline li Result Table Crude1 Regular 2111 111 750 Crudet Diesel 800 0 i Crude2 Super 777 7778 0 B Crude2 Regular 4222 222 750 Crude2 Diesel 0 0 B Crude3 Super 133 3333 0 E Crude3 Regular 3166 667 750 Crude3 Diesel 200 0 The modified Result table The optimal blending has changed after the prices were modified but the optimal advertising expenditure has remained the same IBM ILOG OPL IDE TUTORIALS 61 62 B M ILOG OPL D E TUTORIALS The oil sheet example Describes the oil data spreadsheet the oil sheet project and its execution In this section Description of the example Includes what you will learn and where to find the files The oil data spreadsheet Describes the data stored in Microsoft Excel spreadsheets The oil sheet project Describes the model file in the project The oil sheet data file Describes the data file in the project Executing the oil sheet example Describes the procedure to execute the example and examines the results Viewing the result in the spreadsheet How to display the RESULT table after execution usin
6. After execution the data structure for scalableWarehouse mod is displayed in the Problem Browser LOG OPL IDE TUTORIALS 9e Breakpoints w A 75 s Data 7 1 NbStores 1 NbWarehouses lt Warehouses Fixed lt Stores E SupplyCost ET Capacity Decision variables 2 Ef Open E Supply Decision expressions 2 TotalFixedCost o TotalSupplyCost XY Constraints 2 Ef ctStoreHasOneWarehouse 8 ctOpen 200 50 1 50 10 1 200 12 22 32 42 52 62 72 8292212 567456745674567456 111111111111010101 0 00000000000000000 370 1110 The navigation tools of the IDE are available for your use at this time You can view a model element in a separate table by double clicking it If you click the drop down list at the top you can see the final solution and if the model expresses a MIP problem all the solutions of the pool See Working with the solution pool for details You can select an item and see its property in the Property column See Understanding the Problem Browser in Getting Started with the IDE for details I BM ILOG OPL IDE TUTORIALS 25 Changing a CPLEX parameter value Changing CPLEX parameters is useful to experiment with different values The convenient way is to create a settings file and a different run configuration for each value or set of values you want to test However if you decide eventually that a particular setting is alwa
7. Next time you tune run configurations of the project you will find the corresponding sav file in the directory you have selected You can reuse this file in IBM ILOG CPLEX IBM ILOG OPL IDE TUTORIALS 183 184 BM ILOG OPL IDE TUTORIALS Abort Execution button 89 90 aborting execution 89 Access databases connection to 55 creating a table 56 updating 56 Add Remove Breakpoint button 85 98 addRangeFilter method IloCplex class 163 arrays initialization IBM ILOG Script 96 one dimensional in oil database example 54 one dimensional in oil spreadsheet example 67 asterisks in Engine Log output tab 20 Best Integer value in progress charts of MP models 20 Best Mode value in progress charts of MP models 20 blending problem oil example 48 oilSheet example 64 working with external data 44 blue arrow 86 88 102 breakpoints adding removing 85 98 and Run to Cursor button 89 buttons Continue 104 Debug 85 98 Step Into 89 90 99 102 104 Step Out 101 103 Step Over 85 88 90 99 101 Copyright IBM Corp 1987 2009 C Index call stack 87 cells reading 69 code samples covering dat 110 mulprod dat 82 mulprod main mod 82 nurses mod 118 oil mod 67 oilDB dat 55 oilDB mod 53 oilSheet dat 69 profiler mod 140 scalableWarehouse mod 148 transp4 mod 94 warehouse example 15 conflicts 116 potential 134 Conflicts output tab 119 conflicts when relaxing infeasible models 134 constraint programmin
8. The IDE returns to the running state and completes the solve You will see the shape ofthe green line that represents the best integer solution change as more iterations are made 6 Proceed to the next section of the tutorial ILOG OPL IDE TUTORIALS Examining the statistics and progress chart MP Describes the engine log progress chart and statistics table for MP models In this section The Progress Chart MP models Analyses the results of the solve process displayed as a chart in the IDE The Statistics table MP models Analyses the results of the solve process displayed as statistics in the IDE IBM ILOG OPL IDE TUTORIALS 19 The Progress Chart MP models 20 B M The diagram in the right part of the Statistics tab displays the solve process and results as a chart The vertical axis of this chart is the value of the objective and the horizontal axis is time in seconds The chart below is displayed after a pause in the solve process E Problems E Scripting log Solutions 3 Conflicts Relaxations 4 Engine log Statistics 1 5 Profiler a Statistic Value Best node Best integer Integer solution a solution integer optimal tolerance Constraints 250 1490 Variables 10051 Binary 50 1470 Non zero coefficients 20050 MIP Objective 1 480 tie Nodes 2082 Remaining nodes 84 R 1450 Iterations 18053 Incumbent 1 480 1440 amp Solution pool Count 3 0 2 4 6 8 10 12 14 16 Mean o
9. Flow control script for pool solutions solpoolscript mod main thisOplModel generate cplex solve cplex populate var nsolns writeln Nsolns For ver S 07 esnsolns PS OS st cplex solnPoolNsolns thisOplModel setPoolSolution s writeln wansdtitsexlsmu MUS OMM for writeln Open i S This flow control script objective var i in thisOplModel Warehouses cplex getObjValue s thisOplModel Open i 1 creates and extracts the model and populates the solution pool after a regular MIP solve thisOplModel generate cplex solve cplex populate var nsolns uses the solutions in the model writeln for var s 0 s lt nsolns gets the number of solutions in the solution pool cplex solnPoolNsolns writeln Number of solutions found RUPEE S ORIS BT Sura i thisOplModel setPoolSolution s writeln solution write Open FOr write thisOplModel Open i WEEE der O4 yog writeln 168 IBM ILOG OPL IDE TUTOR S gets the objective values for those solutions TObject Iven My cplex getObjValue s writes the results to the Scripting Log var i in thisOplModel Warehouses Wu ums IALS Executing the flow control script To execute the flow control script 1 Select the warehouse project 2 Right click the run configuration name Solution pool script and choose Set as Default 3 Execute the
10. 2 Right click again and select Run this You could also right click the project name and select Run gt Default Run Configuration The iterations appear one at a time in the Scripting log tab i Problems ict dii E Solutions 7 Conficts Relations i Engine log l Statistics Profiler Solve with capFlour 20 OBJECTIVE 457 Solve with capFlour 21 OBJECTIVE 454 75 Solve with capFlour 22 OBJECTIVE 452 5 Solve with capFlour 23 OBJECTIVE 450 25 Solve with capFlour 24 Upon completion the IDE displays the number of solve iterations in the Engine Log tab See What happens when you execute a run configuration in IDE Reference for details of the execution process IBM ILOG OPL IDE TUTORIALS 83 Purpose of the flow control script 84 B M The script performs iterations to solve the model On each iteration it creates a new instance of the model with a changed value for the variable capFlour to improve the value of the objective function The loop ends when there is no further improvement in the objective value After execution the Engine Log ends as shown below E Problems E Scripting log Solutions Conflicts Relaxations 4 Engine log amp 3 statistics 5 Profiler Tried aggregator 1 time ILP Presolve eliminated 3 rows and 4 columns Reduced LP has 15 rows 27 columns and 51 nonzeros Presolve time 0 04 sec Iteration log jIteration ER Dual objective ss 40 000000 Using
11. Access installed on your computer you can view the contents of any of these tables by simply double clicking the database file in Windows Explorer You should view this file in the copy ofthe project you created when you opened the example using the New Example wizard If you did not change any of the default settings in the New Example wizard that should be in your default workspace at the following location C Documents and Settings lt user gt Application Data ILOG OPL Studio IDE lt version gt oilNoilDB mdb Microsoft amp Access opens the database and displays the tables in alphabetical order Double click the table whose contents you want to see The data structure for the oil database example and the oil sheet example is the same dg oilDB Database Access 2000 file format Open Design J New Objects Create table in Design view Create table by using wizard Create table by entering data a a a l f The tables in the oil database The GasData table The five column table GasData stores the following values for each type of gasoline manufactured ILOG OPL IDE TUTORIALS name demand price octane lead Each row is for one type of gasoline with the product name of the gasoline stored as a character string in the first column The daily customer demand for each type of gasoline is recorded and the price in this table is the sales price The octane rating must be at least the value
12. B E Sifting gt Constraint Programming Os NC RN M Absolute gap for solution pool Relative gap for solution pool Limit on number of solutions kept in pool Solution pool intensity Solution pool replacement strategy Populate solution pool 1 0E75 E BI 1 0E75 ER 100 El RI Automatic INI B Replace the first solution by the most rece Mi E RI E Al Turning on the Populate solution pool option Run the configuration again The Problem Browser displays more solutions for you to examine The number of additional solutions collected relies on a number of associated CPLEX parameters described in Setting solution pool options I BM ILOG OPL ID E TUTORIALS 161 Setting solution pool options 162 B M When you activate the Populate solution pool option you can use the other options of the Mixed Integer Programming gt Solution pool page to change the gap tolerance the number of solutions stored and the criteria on which solutions are substituted for others when the pool has reached its maximal capacity You can also set a limit to the number of solutions generated by the populate phase In the tree on the left select the Mixed Integer Programming gt Solution pool Then modify the value for Limit on number of solutions kept in pool As an example 1 2 3 Set the Basic Configuration as the default run configuration Create a settings file and drag
13. File Edit Navigate Search Run Window Help E Problem 0 Variable e Breakpo C BIE Relaxed solution v Name Value i s Data 17 E 1 MaxWorkTim 40 SkilRequirem Emergency C f Skils Anaesthetics Ca f Departme 7 Emergency Co Y Propertv Value irf eel i 0 giy4 ieo OPL Projects 3 Debug Efi nurses mod 2208113 two shifts in the same time are incompatile A amp nurses Nurses Scheduling model MIP 114 forall s in Shifts amp Run Configurations 115 sum s2 in Shifts incompatShifts s s2 1 3 Basic Configuration default 116 NurseAssignments n s2 lt 1 nurses mod 117 nurses ops B nurses dat Requir lt global max worked time forall n in Nurses ctNurseMaxTimeConstraints NurseWorkTime n lt MaxWorkTime Narse Nurse incompatibility forall lt nl n2 gt in NurseIncompat s in Shif ctNurseIncompatConstraints NurseAssignments n1 s NurseAssignments ry I gt Line Original Relaxed It Problems E scripting log 55 Solutions Conflicts Relaxations 3 5 Engine log Statistics 5 Profiler Element Displaying relaxations for nurses mod When you get such messages after execution of a model the next step consists in Studying the suggested relaxation IBM LOG OPL IDE TUTORIALS 121 122 IBM ILOG OPL IDE TUTORIALS
14. Run a different run configuration that utilizes preprocessing scripts Purpose of the preprocessing scripts Explains how to initialize an array set a CPLEX parameter set an OPL option and set the display of variables Debugging a preprocessing script Describes the successive debugging steps IBM ILOG OPL IDE TUTORIALS 91 Presenting the transportation example 92 B M This is a multicommodity flow problem with cities that supply products and cities that demand products In addition there is a capacity constraint on the connections between the cities One issue in large scale transportation problems like this is that only a fraction of the cities are interconnected Because of this sparsity issue a good representation for this application consists of explicit sets of connections routes and costs of routes as well as the demand and supply information The approach to solving this example is described in detail in Exploiting sparsity in the Language User s Manual This section assumes that you are familiar with this example and the solving strategy as explained in that document The file transp4 mod contains preprocessing scripts to prepare data and options and to display data See Preprocessing statements transp4 mod Preprocessing scripts are execute blocks declared before constraints like this execute Important Any execute statement for preprocessing must precede the objective function in the model file
15. Summarizes the problem and explains what to do and where to find the files Setting up the covering model and data Describes the model and data files Purpose of the postprocessing script Enables you to postprocess solutions by placing an execute statement after the objective Executing a postprocessing script Explains how to execute a run configuration and examine the result in the IDE Postprocessing a feasible solution Discusses changing a language option and adding a settings file before postprocessing IBM ILOG OPL IDE TUTORIALS 105 Presenting the covering example 106 B M The covering example is described in detail in Set covering in the Language User s Manual This section assumes that you are familiar with this integer programming problem and the solving strategy as explained in that document Here is a summary of the problem A set covering problem involves selecting items to fill cover a need In this case the need is to build a house and the items are workers The construction of a house can be divided into a number of tasks each requiring one or more skills such as plumbing or masonry A worker may or may not be able to perform a task depending on his or her skills and the cost of hiring a worker also depends on his or her skills qualifications The problem consists of selecting a set of workers to perform all tasks while minimizing the cost A 0 1 variable is associated with each worker to represent whe
16. linear programming 48 mixed integer programming 13 30 156 multiperiod production planning 79 new instance in script 84 nurses 116 profiling 136 slow or memory consuming elements 139 transportation 91 tuning performance 172 warehouse location 14 modifying parameter values 26 modulus operator 16 monitoring loops 92 103 MP options 181 mulprod main mod production example 80 multicommodity flow problem 92 multiperiod production planning 79 multiple spreadsheets 69 named script statement 110 navigation tools within a model 24 new database table 56 New Example wizard 76 OPL IDE TUTORIALS 187 188 features of 76 Nodes column header in Profiler 150 notification of integer solutions 24 nurses example 116 ODBC database connection through Access 55 placeholder syntax 56 vs Oracle 56 oil blending examples with database connection 47 with spreadsheet connection 63 one dimensional arrays in oil database example 54 in oil spreadsheet example 67 Open Project File button 159 options setting via scripting 96 Oracle 45 placeholder syntax 56 vs ODBC 56 orange status indicator 18 order of Profiler table rows 143 output from postprocessing 112 partial solution See feasible solutions 18 performance tuning tool 172 placeholders in database systems 56 Populate solution pool OPL Language option 161 postprocessing executing 111 output for the covering example 112 script 106 preprocessing scripts 92 ar
17. 0000 0 32 768 0 0000 0 31 160 2 1 19 LOAD DATA C ILOG OPL60 examples oplisteelmill steelmill dat 0 0000 0 28 672 0 0000 0 3 616 0 1 8 INIT nbOrders 0 0000 0 0 0 0000 0 72 0 1 1 INIT nbSlabs 0 0000 0 0 0 0000 0 72 0 1 1 INIT nbColors 0 0000 0 IJ 0 0000 0 72 0 1 1 INIT nbCap 0 0000 0 0 0 0000 0 72 0 1 1 INIT capacities 0 0000 0 0 0 0000 0 1 040 0 1 1 INIT weight 0 0000 0 0 0 0000 0 1 072 0 1 1 INIT colors 0 0000 0 0 0 0000 0 1 088 n 1 1 PRE PROCESSING 0 0000 0 0 0 0000 0 14 152 1 1 8 EXECUTE anonymous 1 0 0000 0 0 0 0000 0 3 952 0 1 4 INIT loss 0 0000 0 0 0 0000 0 2 536 0 1 2 INIT maxCap 0 0000 0 0 0 0000 0 592 0 1 i INIT maxLoad 0 0000 0 0 0 0000 0 592 0 1 i EXECUTE anonymous 3 0 0000 0 0 0 0000 0 272 0 1 1 EXECUTE anonymous 5 0 0000 0 0 0 0000 0 9 760 1 1 2 INIT where 0 0000 0 0 0 0000 0 7 856 0 1 1 INIT totalLoss 0 0000 0 0 0 0000 0 8 976 1 1 2 INIT load 0 0000 0 0 0 0000 0 8 072 0 1 1 EXTRACT packCt 0 0000 0 49 152 0 0000 0 224 0 1 2 INIT packCt 0 0000 0 0 0 0000 0 64 0 1 f INIT colorCt 0 0000 0 0 0000 0 776 0 1 i CP Improve Solution 0 0000 0 0 0 0000 0 0 0 1 1 CP Present Solution 0 0000 0 0 0 0000 0 0 0 1 1 POST_PROCESSING 0 0000 0 0 0 0000 0 256 0 1 1 OPL Basic Configuration 100 8 2 CP models Profiler stee1mill project IBM ILOG OPL IDE TUTORIALS 151 Turning off the Profiler The profiling functionality is controlled by an OPL l
18. 4495 456 888 47955 1 2 INIT Values2 0 0625 995 0 0 0 0625 22 456 440 4795 1 1 INIT Values 0 0156 2 454 656 8 0 0156 6 455 800 4795 1 1 EXECUTE INIT Values3 0 0156 2 0 0 0 0000 0 27 768 3 1 4 INIT Values3 0 0156 2 0 0 0 0000 0 27 320 3 1 3 amp INIT indexes 0 0156 2 0 0 0 0156 6 25 200 3 2 READ_DEFINITION profiler 0 0000 0 0 0 0 0000 0 128 0 1 1 INITr 0 0000 095 0 0 0 0000 0 656 0 1 2 INIT n 0 0000 0 0 0 0 0000 0 104 0 1 1 INIT T 0 0000 0 0 0 0 0000 0 296 0 1 1 EXTRACT profiler 0EAEA1D8 0 0000 0 0 0 0 0000 0 168 0 i 1 CPLEX Solve LP Relaxation 0 0000 095 86 016 295 0 0000 0 86 016 995 2 CPLEX Pre Solve 0 0000 0 0 0 0 0000 0 0 1 1 POST_PROCESSING 0 0000 0 0 0 0 0000 0 256 0 I 1 OPL Basic Configuration 100 s Time threshold set to 10 and memory threshold set to 50 profiler mod Copying Profiler contents to a clipboard Click the Copy contents to clipboard icon at the top right of the Profiler tab to copy the Profiler table and then paste it to a text editor or spreadsheet The following screen shows the Profiler table in Microsoft Excel B C D Time Time Peak Memory Peak Memory Self Time Self Time Local Merr Local Merr Count Nodes 3 0 7344 100 5 533 696 100 0 2812 100 975032 100 LOAD MODEL profile OEAEAID8 0 4531 62 1 740 800 31 0 944 256 97 PRE_PROCESSING 0 4531 62 1 736 704 3196 0 942 904 97 EXECUTE INIT_Val
19. IDE If this is not the case read Getting Started with the IDE first The tutorial uses a manufacturing problem solved by the CP Optimizer engine to describe the statistics and progress chart in the IDE Output window Statistics and progress chart work in a very similar manner for models solved with the CPLEX engine Slight differences can be observed For more information see the topics dedicated to constraint programming in the Language User s Manual ILOG OPL IDE TUTORIALS The steel mill example The steel mill problem consists in building steel coils from slabs that are available ina work in process inventory of semi finished products It is described in The steel mill problem in the Samples manual IBM ILOG OPL IDE TUTORIALS 31 Executing the model in the OPL IDE 32 B M To execute the steelmill example 1 ILOG Select File gt New gt Example and use the New Example wizard to open the steelmill example if you have not already done so To run the model open Run Configurations right click on Basic Configuration and select Run this See What happens when you execute a run configuration in IDE Reference for details Click the Engine Log tab in the Output window and examine its contents as you did in the previous tutorial Click the Statistics tab in the Output window See Examining the statistics and progress chart CP to understand what you see at this stage of the execution process OPL ID
20. Products X lt p c gt in Routes Stepping into a function transp4 mod Stepping out of a lower level function Click the Step Return button to execute the write and writeln statements and step out of the printRoute r function The current instruction becomes cran Rut CS because the loop iteration is completed and so the next instruction is the 1oop statement IBM ILOG OPL IDE TUTORIALS 103 104 B M C 5 7execute DISPLAY function printRoute r write r p j D 60 writeln r e o r e d 61 62 63 writeln Routes 64 for var r in Routes 5 printRoute ir Cr on e e 67 Stepping out of the PrintRoute r function transp4 mod Monitoring a function in a loop To continue execution stopping at each pass through the printRoute r function click the Step Into button repeatedly The routes appear one at a time in the Scripting log Note that the Step Into button can continue iterating through the loop as well as stepping into the function When the loop is completed the statement is also complete and so the model is solved At any point you can continue execution to the end of the script without stopping by clicking the Resume button in the Debug view ILOG OPL IDE TUTORIALS The covering example Presents the example and explains how to execute it and debug the postprocessing script In this section Presenting the covering example
21. The conflict search process looks for a way to remove as many constraints as possible while it stays infeasible Consequently a conflict is the subset of constraints from the infeasible model in which removing any of the constraints makes that set feasible When a conflict is displayed in the Conflicts output window it expresses the necessary change to make the model feasible you must remove or modify at least one of the conflicting constraints Important 1 Be aware that minimality may not be achieved if the search process is stopped by a time limit an unexpected interruption or some similar event 2 If the model happens to contain multiple independent causes of infeasibility it may be necessary for the user to repair one cause and then repeat the process with a further refinement A basic example summarizes the difference still more clearly okena INE Sse ovat intr vr maximize y subject to etit x wed ctor ec 0 This model contains two incompatible constraints To remove this incompatibility you can either change ct1 to x lt 0 this is relaxing the constraint or remove ct1 or ct2 this is removing the conflicting constraint Potential conflicts The CPLEX engine differentiates in infeasible models between identified conflicts as described in this tutorial from the nurses example and possible conflicts It may happen that the engine is not capable of completely proving the conflict In this case it re
22. Working with the solution pool Explains how to access a project solution pool in the IDE and how you can set options and define filters on solution pool generation In this section Purpose and prerequisites Explains what to do in this tutorial and where to find the files The solution pool in the OPL IDE Explains how the solution pool works how to use it from the IDE Problem Browser and how to set options Filtering the solution pool Describes how to write filters by means of IBM amp ILOG Script statements Flow control script and solution pool Describes how to use the IBM amp ILOG Script API to populate the solution pool and use the solutions found IBM ILOG OPL IDE TUTORIALS 155 Purpose and prerequisites 156 B M OPL supports the CPLEX solution pool feature for mixed integer programming MIP models The solution pool is a way of generating and keeping more than one solution toa MIP problem This allows you to evaluate and explore alternative solutions For example you might prefer a solution which also meets a secondary objective over the incumbent Prerequisites The tutorial assumes that you know how to work with projects in the IDE If this is not the case read Getting Started with the IDE first What you are going to do Working with various run configurations of the warehouse project based on different models you will 1 Learn how the IDE supports the solution pool for MIP projects See T
23. all I j IBM ILOG OPL V6 3 IBM ILOG OPL IDE Tutorials Copyright International Business Machines Corporation 1987 2009 US Government Users Restricted Rights Use duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp Copyright COPYRIGHT NOTICE Copyright International Business Machines Corporation 1987 2009 US Government Users Restricted Rights Use duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp Trademarks IBM the IBM logo ibm com WebSphere ILOG the ILOG design and CPLEX are trademarks or registered trademarks of International Business Machines Corp registered in many jurisdictions worldwide Other product and service names might be trademarks of IBM or other companies A current list of IBM trademarks is available on the Web at Copyright and trademark information at http Awww ibm com legal copytrade shtml Adobe the Adobe logo PostScript and the PostScript logo are either registered trademarks or trademarks of Adobe Systems Incorporated in the United States and or other countries Linux is a registered trademark of Linus Torvalds in the United States other countries or both Microsoft Windows Windows NT and the Windows logo are trademarks of Microsoft Corporation in the United States other countries or both Java and all Java based trademarks and logos are trademarks of Sun Microsystems Inc in the United States other countr
24. as it is extracted A constraint may take much more time and memory than another even if it appears very simple in OPL This reflects the fact that the aggregate forall construct and the slicing feature enable you to write very complex sets of linear constraints in a compact OPL formulation Even a simple forall statement may be constructed on top of a huge set and then translated into a lot of constraints in the CPLEX matrix You can see another branch at the top of the tree called CPLEX MIP Optimization which reflects the CPLEX search Different CPLEX suboperations are described You may see relevant information such as the amount of time spent generating cuts and using heuristics to find solutions LOG OPL IDE TUTORIALS Profiler for a CP model For a constraint programming model the extraction and solving information appears as shown in CP models Profiler stee1mil1 project EL Problems scripting log Solutions E Conflicts 1 Relaxations 1 Engine log 5 Statistics x Bera Description Time Time PeakMemory PeakM Self Time Self Ti Local Memory LocalM Count Nodes 1 11 04 3 EXTRACT steelmil OEABD418 1 2969 83 5 795 840 1 1 5 EXTRACT colorCt 1 2969 83 5 595 136 1 2969 830 128 0 111 2 CP Search 0 0781 5 995 328 0 0781 50 994 012 60 1 U CP Initial Propagation 0 0312 2 2 457 600 0 0312 20 2 451 060 147 1 i READ_DEFINITION steelmill 0 0000 0 IJ 0 0000 0 128 0 1 1 LOAD MODEL steelmill OE4BD418 0
25. but all the features described work in the same way with models solved by the CP Optimizer engine Important In this tutorial faster and consuming less memory may apply both to creating the model and to searching for solutions This tutorial gives hints only on how to improve the model creation part For the model solving part the tutorial explains what kind of information the profiler can display Using this information to make the model solve faster falls out of the scope of this documentation In other words this tutorial does not explain how to write a better model that finds an optimal solution faster Prerequisites It is assumed that you know how to work with projects in the IDE If this is not the case read Getting Started with the IDE first What you are going to do The tutorial is based on two different examples Working with the profiler example described in Presenting the profiler example you will solve the model see Executing the profiler model become familiar with the profiling information see Description of the profiling information identify slow or memory consuming elements see Examining the profiling information Then working with the scalable configuration of the warehouse example described in Presenting the scalable run configuration you will solve the model see Executing the scalable run configuration look at the information on model extraction and engine sear
26. example The IDE displays the oil project in the OPL Projects Navigator Open the model file in the editing area Set definitions in the model At the beginning of the model file there are definitions of sets of string values to hold the names of the gasolines and oils Set definitions oi1 mod string Gasolines Lkstrrn g Wonks 25 Tuple definitions in the model These are followed by definitions of tuples for the data as shown below Tuple definitions oi1 mod tuple gasType float demand ic lloyenc joie exp float octane float lead tuple oilType clliexewe exeyee Xen EP 1c lioyeuc joe ate ke float octane float lead Note that these tuple definitions follow the rows in the gas and oi1 data respectively but do not include the name column Tuple arrays in the model The model in OPL then declares one dimensional arrays gas and oi1 containing tuples for the gasolines and oils Tuple arrays oil mod gasType Gas Gasolines oilType Oil Oils IBM ILOG OPL IDE TUTORIALS 67 68 B M Note For data input from Microsoft Excel OPL supports one dimensional arrays of tuples as well as one or two dimensional arrays of int float and string values ILOG OPL IDE TUTORIALS The oil sheet data file Double click the oilSheet dat file in the project tree to see the contents of the data file Data file for the Oil Sheet example 0i1Sheet dat SheetConnection
27. il 2 S 4 5 6 7 9 42 10 21 didt 20 12 Sat 9 10 14 18 11 16 9 389 25 29 Sil 92 3 3 2 t5 Lg 20 1O 9 Ire 9 24 Sy BE E 22 4 26 25 2 26 32 28 30 30 25 23 30 27 32 31 2028228739 14 2 5 18 22 25 29 26 31 23 24 28 31 29 32 24 26 30 driveway moving 2s S Di 2S 30 Sil SZ 32 Si 30 sal yj 27 30 32 ZS SH 3 22 j JL T cake ae ak AR ake AL o2 2 292 02 2 2 3 3r 5k Sr a 1 Ur 0 5 3 3 999 7 94 B M LOG OPL D E TUTORIALS 109 Purpose of the postprocessing script Any execute IBM ILOG Script statement placed after the objective enables you to postprocess the solutions found by the execution process For example in the statement named DISPLAY in covering mod it allows you to write to the Scripting log see Postprocessing script covering mod 110 IBM ILOG OPL IDE TUTORIALS Executing a postprocessing script The covering example defines only one run configuration To execute the run configuration 1 Right click on Run Configurations and select Run gt Basic Configuration default Upon completion the IDE displays the number of solutions found in the Solutions tab See What happens when you execute a run configuration in IDE Reference for details of the execution process 2 Examine the Scripting log At the end of execution the Scripting log contains
28. in GasData OLitype Ov Lionel i eo name 4 o o ia Oieee 1 The preprocessing is done by execute statements in IBM ILOG Script for OPL The transportation example explains such statements Table loading In the oilDB2 mod example you access the one dimensional array right from the database as shown in the following code extract from the data file 0i1DB2 dat Reading database columns to a tuple o11DB2 dat Gasolines Gas from DBRead db SELECT name name demand price octane lead FROM GasData Oils Oil from DBRead db SELECT name name capacity price octane lead FROM UxlDatats ILOG OPL IDE TUTORIALS The oil database data file Double click the oilDB dat file in the project tree to see the contents of the data file Data for the Oil Database example 0i1DB dat DBConnection db access oilDB mdb Gasolines from DBRead db SELECT name FROM GasData Oils from DBRead db SELECT name FROM OilData GasData from DBRead db SELECT FROM GasData OilData from DBRead db SELECT FROM OilData MaxProduction 14000 ProdCost 4 DBExecute db drop table Result DBExecute db create table Result oil varchar 10 gas varchar 10 blend real a real Result to DBUpdate db INSERT INTO Result oil gas blend a VALUES Notice that the data file starts with the DBConnection statement used to connect to the database Note You can have multiple data files and within any of them multipl
29. means that the particular tuning iteration took longer than the fastest iteration run so far Note Please note that the progress of the tuning operation is shown in two different locations in the Engine Log tab and at the right of the IDE s Status Bar The percentages shown in these two locations may not be identical 178 IBM ILOG OPL IDE TUTORIALS Results When the tuning process is completed a new ops file is created and automatically added to the project If you double click it you can see in the editor what values have been modified Depending on your hardware configuration the execution speed may change hence the results of the tuning process may be different If you add the tuning result file to the scalable data run configuration and execute this configuration notice that the execution time is shorter almost reduced by half and that the Engine Log is different IBM ILOG OPL IDE TUTORIALS 179 Tuning with fixed settings 180 B M Sometimes you may want to tune parameters to get the best performance in your own specific context For example in your context the best performance may be instead of the optimal solution a solution that is within a certain gap from the optimal one To achieve this you can pass the performance tuning tool a set of fixed parameters which the tuning process cannot change as they will be used in your model These settings are taken into account as is to calculate the tuni
30. models that appear infeasible after execution In this section Presenting the nurse scheduling example Summarizes the problem and explains what to do and where to find the files Setting up the nurses model and data Describes the elements of the model Executing the nurses project 1 Describes how to observe infeasibility conflicts and proposed relaxations Working on the execution results Describes how to study the conflict and suggested relaxation and change the data to remove infeasibility Executing the nurses project 2 Explains how to observe the new result after changing the data How relaxation and conflict search works Relaxations and conflicts both express the infeasibility of a model and propose steps towards feasibility After you have had hands on experience with the nurse scheduling example learn how to differentiate between Relaxations and Conflicts IBM ILOG OPL IDE TUTORIALS 115 Presenting the nurse scheduling example 116 B M The tutorial assumes that you know how to work with projects in the IDE If this is not the case first read Getting Started with the IDE Note You can also search for relaxations and conflicts using the IBM ILOG Script methods printRelaxations and printConflicts See Searching for relaxation and conflicts The nurses example The nurses example describes a nurse scheduling problem the hospital Human Resources department needs to create work schedules for nurs
31. per test set that is suite of models applicable in tuning Options are Any non negative number Default 10000 182 IBM ILOG OPL IDE TUTORIALS Temporary tuning files You can save the temporary sav files created by the tuning process to disk to examine their content later To save the temporary tuning files 1 Add a settings file as explained in Adding a settings file in Getting Started with the IDE 2 Make sure you add it to the run configurations you want to tune 3 In the new settings file check the option Language gt General gt Keep temporary tuning files 4 Enter a target directory for the temporary files o warehouse tuning ops x Type parameter description filter Display width 200 ur 4 Mathematical programming gt Constraint Programming Language Big map naming threshold 100 General Run Display precision 4 m e e a Database update batch size 256 m e 9 9 9 Path for resolving resources SOPLROOT lib Display array indices o Display component names L1 Wy m B iiij le ie Display one component per line o Force element usage L1 Relaxation level All variables and labeled constraints Directory for temporary tuning files C MyProjects warehouse tuning_files Tii 9 Keep temporary tuning files M Keeping temporary tuning files
32. run configuration Notice that The result of the script execution is reported in the Scripting log The number of solutions found is written at the top of the Scripting log tab You cannot see the list of solutions from the Problem Browser Ifyou add an ops file and check the option Populate solution pool it is not taken into account because script statements prevail over IDE settings For more information on the solution pool in general see the CPLEX documentation in particular the specific chapter in the CPLEX User s Manual on the IBM ILOG Script API for the solution pool see the IBM ILOG Script Reference Manual IBM ILOG OPL IDE TUTORIALS 169 170 IBM ILOG OPL IDE TUTORIALS Using the performance tuning tool Describes how to improve the combination of parameters for the CPLEX part of your model s In this section Purpose and prerequisites Introduces the CPLEX performance tuning tool and tells you where to find the files for the tutorial How performance tuning works Describes the CPLEX performance tuning tool How to use performance tuning in the IDE Two ways of using the performance tuning tool first without fixed settings then by specifying the settings you want to use IBM ILOG OPL IDE TUTORIALS 171 Purpose and prerequisites 172 B M The purpose of the CPLEX performance tuning tool is to find the best combination of parameters for the CPLEX part of your model s that can be
33. scripts 98 Run to Cursor button 89 stepping into a loop 102 decision variables table view in Problem Browser 24 IBM ILOG OPL IDE Description tree in Profiler output tab 142 diversity filters for the solution pool 163 division div operator 16 Dual Simplex algorithm output 97 ECMA 262 standard 76 editing area navigation 24 efficient models labeling constraints 132 ellipsis in call stack 99 end of execution 89 end of line 82 Engine Log CPLEX node log 22 Engine Log output tab stars 20 Engine Log output tab CP engine steel mill example 39 error checking read only spreadsheet 71 examples covering 105 multiperiod production planning 79 nurses 116 oil database 47 oil sheet 63 profiler 140 scalable warehouse 148 transportation 91 execute IBM ILOG Script block 106 110 covering example 108 for preprocessing 92 transportation example 94 using the function keyword 97 executing flow control script 83 oil database example 58 oil sheet example 71 preprocessing scripts 95 projects 18 119 141 149 scripts 111 112 execution abort 89 events description 18 slow 136 139 external data 44 extraction and solving info in Profiler output window 150 feasible solutions TUTORIALS postprocessing 112 files mulprod_main mod 80 oil example 48 oilSheet example 64 profiler example 136 read only spreadsheet 71 scalableWarehouse example 148 warehouse example 14 136 filtering solution pool 163 fixed set
34. sheet oilSheet xls Gasolines from SheetRead sheet gas A2 A4 Oils from SheetRead sheet oil A2 A4 Gas from SheetRead sheet gas B2 E4 Oil from SheetRead sheet oil B2 E4 MaxProduction 14000 ProdCost 4 a to SheetWrite sheet RESULT A2 A4 Blend to SheetWrite sheet RESULT B2 D4 The data file starts with the SheetConnection statement used to connect to the spreadsheet Note You can have multiple data files and within any of them multiple connections to spreadsheets Connecting to the spreadsheet from OPL The connection is established by the following statement Connecting to a spreadsheet MS Excel SheetConnection sheet oilSheet xls The name of the spreadsheet file in quotes is passed as an argument Note You do not need to specify the full path name Relative paths are resolved using the directory of the current dat files Reading from the spreadsheet Reading spreadsheet columns You can read data from a column in any sheet into an OPL array using the SheetRead statement as in the data file oilSheet dat Reading spreadsheet columns oilSheet dat Gasolines from SheetRead sheet gas A2 A4 Oils from SheetRead sheet oil A2 A4 IBM ILOG OPL IDE TUTORIALS 69 70 B M Note that the cells are read from 2 upward as the name of the column is not stored Reading spreadsheet cell ranges You can read blocks of cells from a spreadsheet into an OPL array u
35. solve process for scalableWarehouse Statistic Value g solution integer optimal tolerance Constraints 250 5 Variables 10051 Binary 50 Non zero coefficients 20050 MIP Objective 1 480 Nodes 2082 Remaining nodes 84 Tterations 18053 Incumbent 1 480 5 Solution pool Count 3 Mean objective 1 500 MP models results for scalableWarehouse mod The top level of the Statistic tree indicates the solving engine CPLEX You see certain statistic values change dynamically as the solving takes place For most algorithms the statistics items are the CPLEX problem Number of constraints and variables in a format similar to that of the Engine Log with various characterizations Number of non zero coefficients Number of quadratic constraints and coefficients when applicable the presolve stage not shown in the scalableWarehouse example Number of rows and columns removed when applicable the solve stage with the names of the algorithms used such as MIP Barrier Simplex and so on with the corresponding statistics for each of them IBM ILOG OPL IDE TUTORIALS 21 Examining the engine log 22 B M The Engine Log tab in the Output window shows the CPLEX node log when an LP model is solved 2 Problems E Scripting log Solutions 74 Conficts Relaxations Engine log 53 Statistics S Profiler fried aggregator 1 time IMIP Presolve eliminated 0 rows and 1 columns R
36. stored and the lead content must not exceed the value stored The following GasData table is the table as you see it in Microsoft Access BB GasData Table se NECS NNUS ERN RECEN NUR Regular 2000 n Diesel 1000 50 6 1 co The GasData table The OilData table The five column table oilData stores the following values for each type of crude oil name capacity price octane lead Each row is for one type of crude with the name of the crude stored as a character string in the first column The capacity figure represents the amount that can be purchased each day and the price is the purchase price The other columns store the octane rating and the lead content The following oilData table is the table as you see it in Microsoft Access OilData Table a UU CN RN TN a N Crude2 s Crude3 5000 25 8 3 The OilData table The Result table The table Result gives the results in rows for each crude gasoline combination It shows the blend as the number of barrels of each crude used for each type of gasoline and the amount a spent on advertising the type of gasoline IBM ILOG OPL IDE TUTORIALS 51 52 B M Result Table B Crude1 Regular 2111 111 750 Crude1 Diesel 800 0 Crude2 Super 777 7778 0 ES Crude2 Regular 4222 222 750 Crude2 Diesel 0 0 Crude3 Super 133 3333 0 H Crude3 Regular 3166 667 750 Crude3 Diesel 200 0 The Result table The results for the data s
37. xem Upper cutoff Limits Tolerances 2 6 Mixed Integer Programn General Strategy Limits Tolerances Cuts Solution pool Solution polishing 3 6 Barrier General Limits Network General Tolerances B S Sifting General amp amp Constraint Programming Propagation Control Ji d Jl Changing the value of a CPLEX parameter You can also create a specific run configuration as explained in Creating and executing a different configuration in Getting Started with the IDE Click the Run button gt to rerun the same configuration Scalable data If you are prompted to save click OK Execution ends almost immediately and the progress chart reflects this fact Note The Run button re executes the last executed configuration IBM ILOG OPL IDE TUTORIALS 27 28 B M E Problems E Scripting log Solutions 34 Conficts 2 Relaxations 5 Engine log Statistics 2 5 Profiler ry Statistic Value Best node Best integer Integer solution solution integer optimal tolerance Constraints 250 amp Variables 10051 Binary 50 1580 Non zero coefficients 20050 amp MIP Objective 1 490 Nodes 0 Pied Remaining nodes 2 Iterations 505 Incumbent 1 490 1440 amp Solution pool Count 2 0 54 0 56 0 58 0 6 0 62 0 64 0 66 0 68 0 7 0 72 0 74 0 7 Mean objective 1 510 Time seconds MP models Progress Chart New
38. 00 0 168 0 1 1 CPLEX Solve LP Relaxation 0 0000 0 86 016 2 0 0000 0 86 016 9 5 1 2 CPLEX Pre Solve 0 0000 0 0 0 0 0000 0 0 0 1 1 POST_PROCESSING 0 0000 0 0 0 0 0000 0 256 0 1 1 OPL Basic Configuration 100 e Profiling information for the profiler example The Description tree Most categories below the root item include two important kinds of item as shown in Execution tree items Execution tree items Script block execution EXECUTE block name Data initialization INIT data element name Then for each execution step the elements listed below are displayed in columns 142 IBM ILOG OPL IDE TUTORIALS Profiling information measured for each execution step Information for each execution Definition The total time consumed by the task Percentage of time as a proportion of the total time Peak Memory The maximal memory used to process the OPL problem See also the Glossary Percentage of peak memory as a proportion of the total memory Self time The time used by the task minus the time used by the subtasks Percentage of self time as a proportion of the total time Local Memory The memory usage observed by comparing the start and the end of a step See also the Glossary Percentage of local memory as a proportion of the total memory The number of times that same node is repeated on this tree level The number of nodes in the branch starting at this node Proce
39. 04 2 CPLEX Solve LP Relaxation 0 3906 o 0 0 3906 64 1 721 0 502 1 CPLEX Solve LP Relaxation 0 3906 o 0 0 3906 64 195 0 377 1 CPLEX Solve LP Relaxation 0 3281 626 688 2 0 0000 0 1 082 149 6 122 2 CPLEX Solve LP Relaxation 0 3281 626 688 2 0 3281 54 1 082 149 6 122 1 CPLEX Heuristics 0 3125 o 0 0 1094 18 20 480 0 42 3 CPLEX Solve LP Relaxation 0 2031 o 0 0 0000 0 303 0 337 2 CPLEX Solve LP Relaxation 0 2031 o 0 0 2031 494 0 207 1 CPLEX Generating Cuts for Root Node 0 1875 0 0 0 1562 1 585 152 8 1 7 CPLEX Generating Cuts for Root Node 0 1562 2 703 360 8 0 0469 13 1 7 LOAD_MODEL scalablewarehouse 0EB11270 AA INIT TotalSupplyCost 0 1250 888 832 0 0000 4 1 4 OPL Scalable data 100 eD Profiling information for the scalable configuration of the warehouse example You can see the two columns Count and Nodes The Count column displays the number of times that same node is repeated on this tree level This count is 1 most of the time except for extractions of labeled leaf constraints inside a forall statement and during the CPLEX search The Nodes column displays the number of subnodes in the branch starting at this node The node count for leaves is 1 In the Description tree you can see an item called EXTRACTING model name random number This branch of the execution tree includes all of the extraction phase of the model from OPL to the CPLEX engine Each labeled constraint is shown as a leaf
40. 2 1 4 1 6 1 8 2 Time seconds CP models progress chart route project The progress chart shows the variation of the objective The yellow points show when solutions are found and the green line basically follows these points showing the evolution of the best solution found over time IBM ILOG OPL IDE TUTORIALS 37 The statistics table CP models 38 B M The statistics table and progress chart work in a very similar manner for models solved with the CP Optimizer engine However take a look at the route example to observe the differences Click the Statistics tab after executing the Basic Configuration for the route project The statistics are on the left t Problems EJ Scripting log Solutions 7 Conflicts Relaxations i Engine log Statistic Value a Constraints 64 Variables Tt Memory usage 960500 Choice points 7059 Number of solutions 17 Number of branches 13798 Number of fails 6833 Objective 10 001 CP models Statistics table route project The top level of the Statistic tree indicates the solving engine CP You see certain statistic values change dynamically as the solving takes place The statistics items are Number of constraints after initial propagation Number of variables Memory usage including after initial propagation Number of choice points Number of fails The objective Click on the Solutions tab to see the number of solutions obtained You can change constr
41. 39 Presenting the profiler example eeessseeeeeeeeeeeeeeeee eene nennen nennen trennen nter 140 Executing the profiler model 5 2 25 22 hs hte a a Een ee eet 141 Description of the profiling information mem 142 Examining the profiling information sesseeennenm nmm enne 146 Examining model extraction and solving ssessseeseeeneen nennen eene nnnm 147 Presenting the scalable run configuration senem 148 Executing the scalable run configuration eseeeeeeenm een eenm emn ennnee 149 Examining the extraction and search information essennm eme 150 Turnirig off the Profiler issiron Sods prt reet et eerie edt et tae 152 Drawing ConGclusiOris 4 2 ett fiit ett guerre cii d e e re rs ede rtt da etel 153 Working with the solution pool eere nennen nennen nennen nennen nnns 155 Purpose and prerequisites eene te aE E aeaa aa Ea aa AAE EE RU RIEN EEE AAAA EEEa MUR Sipain irekin 156 The solution pool inthe OPL DE a eea e ie Hen OPER EP RR ERE DRE aeiiae 157 How the solution pool works sessesseenneeeneeenn rene nn nennen nennen nnns 158 Examining pool solutions in the Problem BrowSet cessceeesseeeseneeeeeneeeeeeneeeseneeeeeeneeeseneeerenaeees 159 Obtaining More Solutions on hese ete ertt tee i aed eee eel 161 Setting solution pool options
42. 5 486 0 70s rte 5 94 10 042 6 000 1 rte 5 85 F 10 042 7 000 1 rte 4 96 10 042 8 000 T rte 3 141 F 10 042 8 701 1 03s rte 5 25 10 030 Time 1 03s Average fail depth 5 Memory usage 814 8 Kb Rranche s Non fixed Rranch decision Rest Engine Log for the Steel Mill example default CP settings The first line of the log indicates the type of problem along with the number of decision variables and constraints in the model In the steel mill example there is an objective included in the model so the problem is reported to be a Minimization problem When the model does not include an objective the problem type is reported as a Satisfiability problem In this example we have one line each 50 branches as indicated by the parameter set in the model steelmill mod cp param LogPeriod 50 The next three lines of the log provide information regarding the initial constraint propagation The Initial process time is the time in seconds spent at the root node of the search tree where the initial propagation occurs This time encompasses the time used by the optimizer to load the model called extraction and the time spent in initial propagation IBM ILOG OPL IDE TUTORIALS 39 40 B M The value for Log search space provides an estimate of the size of the depth first search tree this value is the log base 2 of the products of the domains sizes of all the decision variables of the problem Typically the esti
43. DE ILOG OPL I 0000000000000000 000000000 IBM 0000000000000000 000000000 106 107 108 Executing the nurses project 2 128 B M After you have changed an assignment value as shown in Changing the data you are going to execute the project again and see the new result To observe the new result 1 Right click on the nurses project and select Run gt Basic Configuration Click OK in the popup to save the modified file The Conflicts and Relaxations tabs are now empty while the Solutions tab displays the solutions found You now get a feasible solution with cost 24950 as shown below E Problems E Scripting log i Solutions 2 gt z Conflicts Relaxations amp Engine log Statistics 5 Profiler solution optimal with objective 24950 CostByDepartments 15458 9492 NurseAssignments 1111000001000011000000000000 000000 0 0D000100000000000000001100000100 i0 111 10000001010010000000000000000001 Feasible model after change in data You can also see that Anne is assigned to Emergency on the Monday 8 to 12 shift not to Consultation To view Anne s assignment do as follows In the Problem Browser scroll down in the Name column to Decision variables NurseAssignments as shown ILOG OPL IDE TUTORIALS w A o amp amp Data 17 m Decision variables 8 15458 9492 Ef NurseAssignments 1111000001000011000 Ef AllocationByDepartments 106 90 E NurseWo
44. E TUTORIALS Coloring of CP keywords and functions in the IDE If you double click steelmill mod to open it in the IDE editor you will notice that the first support of constraint programming in the IDE is the colored names of the functions used in the model to define specialized constraints for example pack on line 48 IBM ILOG OPL IDE TUTORIALS 33 34 B M ILOG OPL D E TUTORIALS Examining the statistics and progress chart CP Describes the statistics and progress chart for CP models In this section Statistics Describes the contents of the CP Statistics tab displayed in the OPL IDE The progress chart CP models Analyses the results of the solve process displayed as a chart in the IDE The statistics table CP models Analyses the results of the solve process displayed as statistics in the IDE IBM ILOG OPL IDE TUTORIALS 35 Statistics 36 IBM ILOG OPL IDE The Statistics tab of the IDE Output window also provides information on the search such as number of choice points fails and memory usage When you click the Statistics tab in the Output window you can see the CP Optimizer solving statistics E Problems E Scripting log Solutions 7 Conficts Relaxations Engine log f Statistics amp 55 Profiler ELI Statistic Value ei Objective Solution Proven solution Constraints 22202 oe Variables 222 Memory usage 9496776 4 Choice points 139 Number of solutions i Number o
45. E displays the nurses project in the OPL Projects Navigator Open the model in the editing area Since this is a rather long model it cannot be shown entirely Scroll down or resize the main window to see more of it The model instance nurses mod contains the following elements nurses nurse shifts nurse teams maximal and per nurse work time nursing skills requirements hospital departments department incompatibilities vacations required assignments Double click nurses dat in the OPL Projects Navigator to display the data instances associated with this model in the editing area Notice that the Outline window presents a convenient view of the model or data elements 118 BM ILOG OPL IDE TUTORIALS Executing the nurses project 1 The nurse scheduling project has been designed with infeasible data The IDE lets you know when a project is infeasible proposes relaxations and displays conflicts to help you make it feasible In this section you are going to execute the model and observe infeasibility 1 Double click on the settings file nurses ops to open it in the editing area 2 In the displayed settings file select Language gt Run in the left panel and make sure that the Display relaxations and Display conflicts options are checked These options which are turned on by default tell the IDE to compute and display suggested relaxations and conflicts when they exist in the Conflicts a
46. LOG Script for OPL in the Language Reference Manual the Reference Manual of IBM ILOG Script Extensions for OPL for full details of the language Note You can use the features of the New Example wizard to search for distributed OPL examples that use IBM ILOG Script or OPL Flow Control Script or other features or techniques you are interested in For example the following screenshot shows the New Example wizard displaying its Sorted by Feature tab displaying some of the examples that show off OPL Flow Control Script ILOG OPL IDE TUTORIALS P New Example Example Project 9 You must select an example Sorted by Complexity Sorted by Feature Sorted by Industry Sorted by Technique Choose an example Press F1 for more information typefittertext OPL Flow Control Script All Examples All Models Basketball Scheduling Call Traffic Optimization conflict iterator convert_example Crew scheduling Mi Choose copy location C Documents and Settings user Appication Data ILOG OPL Studio IDE 6 2 Similarly you can use the New Example wizard to search for examples by Complexity Industry represented or programming Technique used IBM ILOG OPL IDE TUTORIALS 77 Features of IBM ILOG Script for OPL IBM ILOG Script for OPL enables you to Add preprocessing instructions to prepare data for the model Control the flow while the model is solved Set CPLEXG parameters CP Optimizer parameters CP Optimi
47. MIP gap tolerance scalableWarehouse mod There are fewer solutions in the Solutions tab and in the Problem Browser list than when the gap tolerance was not user defined You can now close the warehouse example see Closing projects in IDE Reference for details if necessary LOG OPL IDE TUTORIALS Understanding solving statistics and progress CP models Shows how the IDE displays a dynamically updated progress chart for a constraint programming example that takes a few seconds to solve In this section Purpose of the tutorial Describes the type of model used The steel mill example Summarizes the problem Executing the model in the OPL IDE Explains how to solve the steel mill problem and examine the results Coloring of CP keywords and functions in the IDE Constraint programming in the OPL IDE is distinguished by the colored names of the functions Examining the statistics and progress chart CP Describes the statistics and progress chart for CP models Examining the engine log Describes the contents of the CP engine log displayed in the OPL IDE Changing a CP parameter value Explains how to change a constraint programming option in the IDE IBM ILOG OPL IDE TUTORIALS 29 Purpose of the tutorial 30 B M In this tutorial you will see how the IDE displays a dynamically updated progress chart for a constraint programming CP example The tutorial assumes that you know how to work with projects in the
48. Relaxations and Conflicts In this section Relaxations Provides a definition of a relaxation Setting the relaxation level Explains how to set the relaxation level in the OPL IDE Conflicts Discusses conflicts and potential conflicts IBM ILOG OPL IDE TUTORIALS 131 Relaxations In this context a relaxation is a modified model where some bounds of variables and or constraints have been made wider than in the first version For example an integer variable with the original bound 0 100 could be relaxed to 0 200 orarange constraint expr lt 10 could be relaxed to expr lt 12 The relaxation search process looks for a way to make the model and its data more flexible so that the problem becomes feasible while keeping modifications to a minimum In other words the suggested relaxation in the Relaxations tab is a sufficient minimal change to make the model feasible More about constraint relaxation More specifically only constraints that have been labeled are taken into account for possible relaxation and conflicts As variables are systematically named they are always considered by the search process Constraints however may be unlabeled If you choose not to label the constraints in your model they will not be taken into account for relaxation or conflict search In this case only the variables will be affected by the relaxation process which may lead to surprising suggestions Moreover some existing conflicts m
49. SPLAY function printRoute r write Ne aS ea writeln r e o r e d e CO C C C co J gt W N F2 OLW writeln Routes for var r in Routes printRoute r Al J yy J Stepping out of an execute function transp4 mod 1 Click the Step Over button to execute the instruction If you open the nodes in the call stack you can see the CPLEX parameter setting listed for the predefined cplex object 2 Click Step Over four more times The current instruction is now printRoute r Note that Step Over does not move to the statement within the function because it is at a lower level Stepping into a function The Step Into button allows you to step into a function Use it to step to the first statement or to the instruction after the current one if there is no function called To step into the printRoute r function click the Step Into button ILOG OPL IDE TUTORIALS The IDE executes the current instruction and the blue arrow in the margin moves to the first line in the function Wolter A ICE Slexecute SETTINGS 52 settings displayComponentName true 53 settings displayWidth 40 writeln Routes Routes S7execute DISPLAY function printRoute r write r p 4 writeln r e o r e d writeln Routes for var r in Routes printRoute ir 68 string Orig p in Products lt p c gt in Routes 69 string Dest p in
50. Working on the execution results Describes how to study the conflict and suggested relaxation and change the data to remove infeasibility In this section Studying the suggested relaxation Suggests places where you can change the data or the way constraints are expressed to remove incompatibilities Studying the suggested conflicts Explains the conflict in the model and how to avoid it Changing the data Shows how to change the data in the nurses dat file IBM ILOG OPL IDE TUTORIALS 123 Studying the suggested relaxation 124 B M When a model proves infeasible the IDE suggests the places where you can change the data or the way constraints are expressed so as to remove the incompatibilities l Note Only ranged constraints are relaxable Logical constraints are not Click the Relaxations tab For the nurses example you should see what is shown below Problems E Scripting log Solutions Conflicts Relaxations amp 5 Engine log Statistics 5 Profiler Line Original Relaxed Element ctRequiredAssignmentConstraints lt Anne gt lt Emergen Suggested relaxation nurses mod The proposed relaxation consists in changing the bound of the given constraint to 0 1 instead of 1 1 The relaxation refers to the constraint on required assignments respect required assignments forall n in Nurses s in Shifts RequiredAssignments n s 1 ctRequiredAssignmentConstraints NurseAssignme
51. abase rows You can read rows from any table into an OPL tuple set using the DBRead statement as shown in oilDB dat Reading database rows oilDB dat GasData from DBRead db SELECT FROM GasData OilData from DBRead db SELECT FROM OilData Note that the data file also initializes some variables directly it does not only take data from the database Creating a new table and updating the database At the end of the optimization process you need to store the optimal blends and advertising expenditures in a new database table Use the OPL statement DBExecute in the data file to create a new table called Result which has four columns corresponding to the fields in the tuple Result With Microsoft Access the instructions to delete the Result table if it exists and then re create it are Deleting and recreating the Result table DBExecute db drop table Result DBExecute db create table Result oil varchar 10 gas varchar 10 blend real a really You can then insert the oil gas blend and a arrays as columns in the table Result using a DBUpdate statement With Microsoft Access the insertion is made by the instruction Creating a Result table Result to DBUpdate db INSERT INTO Result oil gas blend a VALUES The difference between the DBUpdate instruction with ODBC Microsoft Access and the DBUpdate instruction with Oracle lies in the different syntax for the placeholders inside the SQL req
52. ain mod 66 var curr Infinity var basis new IloOplCplex var ofile new IloOplOutpu The call stack in the Debug view mulprod main mod 4 5 var best 6 IBM ILOG OPL IDE TUTORIALS 87 88 B M 2 The Variables view shows the content of the selected call frame In this example there is only one call frame er xt best undefined produce a IloOplMain IloOplModel capFlour 20 ofile undefined basis undefined def undefined status 0 curr undefined data undefined with object Object this object Object E bd Many of the variables in this example are marked undefined because they are not decision variables Stepping to the next instruction When you execute a run configuration in debugging mode the Debug view is displayed to enable you to use the stepping buttons in its toolbar o UP aj LRF Debug toolbar The Step Over button allows you to step through the script instruction by instruction executing each instruction as you go Use it to step over a function and go to the statement after the function call an instruction and go to the instruction after it When you are stepping in a script the blue arrow in the margin keeps track of the current position To step to the next instruction 1 Click the Step Over button ILOG OPL IDE TUTORIALS Note that the Step Into button The IDE executes the current instruction an
53. aint programming parameters by changing values in the Constraint Programming page ofthe settings editor See also Constraint programming options in IDE Reference ILOG OPL IDE TUTORIALS Examining the engine log When you click the Engine Log tab in the Output window you can see the CP Optimizer log 2 Problems scripting log Solutions 7 Conficts Relaxations 4 Engine log 3 Statistics Profiler Minimization problem 11 variables 64 constraints OptimalityTolerance 0 RelativeOptimalityTolerance 0 Initial process time 0 01s 0 00s extraction 0 01s propagation Log search space 144 4 before 127 4 after Memory usage 427 6 Kb before 459 6 Kb after Variables fixed i3 Branches Non fixed Branch decision Best 1 000 3 rte 1 486 1 042 0 17s rte 5 129 75 761 2 000 1 rte 5 83 F 75 161 2 159 0 29s rte 5 129 58 723 2 225 0 31s rte 5 96 24 050 3 000 Zz rte 4 370 24 050 3 274 0 38s rte 5 92 19 505 4 000 Z rte 5 340 19 505 4 360 0 51s rte 5 96 16 595 I 4 365 0 60s rte 4 0 13 297 4 395 0 61s rte 5 92 11 124 4 411 0 61s rte 5 65 10 496 4 437 0 62s rte 5 178 10 240 4 446 0 63s rte 5 25 10 082 5 000 2 cost 2 11 443 F 10 082
54. ample transp4 mod f oste Cost Roues ust ato cle ost tee eD TERU tSS lE This cost array is used in the objective which aims to minimize the sum of transportation costs along all routes See also As generic indexed arrays in the Language Reference Manual However you can also use a preprocessing execute block as shown in the following code extract which contains a script named INITIALIZE Preprocessing script initializing an array transp4 mod float Cost Routes execute INITIALIZE for var t in TableRoutes Cost Routes get t p Connections get t o t d t cost Setting a CPLEX parameter The script named PARAMS sets a CPLEX parameter for the algorithm Preprocessing script setting a CPLEX parameter transp4 mod This parameter sets a time limit on each call to the optimizer See Changing CPLEX parameters in the Language User s Manual Setting an OPL option The script statement named SETTINGS sets the display of the component name on 40 characters ILOG OPL IDE TUTORIALS Preprocessing script setting an OPL option transp4 mod Setting the display of variables The script statement named DISPLAY displays the routes in the Routes tuple set in the format product origin gt destination The DISPLAY script uses a function to do this You can see this display of the routes in the Scripting Log tab Preprocessing script displaying variables transp4 mod execute DISPLAY function pr
55. anches the number of branches explored in the binary search tree Non fixed the number of uninstantiated not fixed model variables Branch decision the decision made at the branch currently under consideration by the optimizer Best the value of the best solution found so far in the case of an optimization problem The final lines of the log provide information about the entire search after the search has terminated This information about the search includes Solution status the conditions under which the search terminated Number of branches the number of branches explored in the binary search tree Number of fails the number of branches that did not lead to a solution Total memory usage the memory used by IBM ILOG Concert Technology and the IBM ILOG CP Optimizer engine Time spent in solve the elapsed time from start to the end of the search displayed in seconds Search speed average time spent per branch The CP Engine Log enables you to trace the propagation see Changing a CP parameter value ILOG OPL IDE TUTORIALS Changing a CP parameter value Changing CP Optimizer parameters is useful to experiment with different values The convenient way is to create a settings file in the OPL IDE and a different run configuration for each value or set of values you want to test However if you decide eventually that a particular setting is always needed for the model concerned you can even set the parameter within th
56. anguage option which tells the IDE to compute and display the profiling information in the Profiler tab This option is turned on by default but you can turn it off to save execution time and memory To turn off the profiler 1 Create an ops file as explained in Adding a settings file in Getting Started with the IDE and add it to the run configuration drag and drop 2 Click Language gt Run 3 Uncheck the Collect profiling information box as shown below a Type parameter description filter Error limit 50 B S E Mathematical popas Warning limit 50 B Al gt Constraint Programming amp Language Postprocess feasible solutions L1 E RI General Rin Display solution BER Display relaxations E I Display conflicts E RI 9 Collect profiling information LI E a Engine log file E A Export format No export x 8 A Turning off Collect profiling information 152 IBM ILOG OPL IDE TUTORIALS Drawing conclusions The Profiler can help you improve your model so as to reduce or eliminate slow or memory consuming structures For example in profiler mod we would recommend using the third construct Likewise in scalableWarehouse mod you might want to use the optimization part of the Description tree to fine tune the CPLEX search by changing some CPLEX parameter values IBM ILOG OPL IDE TUTORIALS 153 154 BM ILOG OPL IDE TUTORIALS
57. as oil RESULT The oilSheet spreadsheet IBM ILOG OPL IDE TUTORIALS 65 66 B M The gas data Click the sheet gas if it is not visible when you open oilSheet xls The five columns in gas store the following values for each type of gasoline manufactured name demand price octane lead Each row is for one type of gasoline with the product name of the gasoline stored as a character string in the first column The daily customer demand for each type of gasoline is recorded and the price in this table is the sales price The octane rating must be at least the value stored and the lead content must not exceed the value stored The oil data The five columns in oi1 store the following values for each type of crude oil name capacity price octane lead Each row is for one type of crude with the name of the crude stored as a character string in the first column The capacity figure represents the amount that can be purchased each day and the price is the purchase price The other columns store the octane rating and the lead content The following graphic shows the oi1 spreadsheet as you see it in Microsoft Excel Ell oilSheet xls nml x Cap acit H rice octane 5000 45 Crude Crude2 5000 35 6 2 5000 25 8 3 M 4 gt digas hoil lt RESULT J4 Ifz The oil spreadsheet ILOG OPL IDE TUTORIALS The oil sheet project Use the File gt New gt Example menu command to open the oil
58. ay not be found This is another reason why labeling constraints is a recommended practice see Constraint labels in the Language Reference Manual 132 IBM ILOG OPL IDE TUTORIALS Setting the relaxation level You can set whether you want OPL to relax only the labeled constraint or also the variables To set the relaxation level Inthe settings file nurses ops click Language General and choose an option from the Relaxation level list By default both variables and constraints are relaxed You can choose to relax only labeled constraints nurses dat nurses mod nurses ops 3 ELI Type parameter description filter Tij Display width Mathematical programming Constraint Programming Propagation Control Big map naming threshold 2000 Search Control General Aij Display precision 4 tl el pir lel Database update batch size 256 F Tolerances Path for resolving resources OPLROOT lib Limits Log Control Display array indices o w m e amp Language General pi Sj Display component names Oo Run Display one component per line 3 a Force element usage Relaxation level 3 mg qi Directory For temporary tuning Files ijj a Keep temporary tuning files Setting the relaxation level IBM ILOG OPL IDE TUTORIALS 133 Conflicts
59. bjective 1 500 Time seconds MP models Progress Chart at feasible solution scalableWarehouse mod The shapes of the lines on the chart depend on exactly when you pause execution the progress chart shown above is just an example of a first pause The progress chart shows the variation of the best node and best integer values and highlights the integer values found during the search The green line shows the evolution of the Best Integer value that is the best value of the objective found that is also an integer value The red line shows the evolution of the best value of the remaining open nodes not necessarily integer when moving from one node to another This gives a bound on the final solution The yellow point indicates a node where an integer value has been found These points generally correspond to the stars asterisks in the Engine Log See also the Engine Log tab The values in the Value column are dynamic and are updated every second they change to indicate how the algorithm is progressing The values in the Statistic frame are static they indicate the model characteristics Since one feasible solution has been found for scalableWarehouse mod this is listed in the Solutions tab ILOG OPL IDE TUTORIALS The Statistics table MP models The table in the left part of the Statistics tab reflects the contents of the Engine Log hierarchically as a tree The table shown below is displayed at the end of the
60. ble warehouse has a fixed maintenance cost and a maximum capacity specifying how many stores it can support Each store can be supplied by only one warehouse and the supply cost to the store differs according to the warehouse selected The application consists of choosing which warehouses to build and which of them should supply the various stores in order to minimize the total cost which is the sum ofthe fixed costs and the supply costs The model instance used in this section considers 50 warehouses and 200 stores The fixed costs for the warehouses are all identical and equal to 10 The warehouse project folder contains the model scalableWarehouse mod ILOG OPL IDE TUTORIALS The scalable warehouse project You will now take a look at this project in the IDE Use the File gt New gt Example menu command to open the warehouse example If you need a reminder of how to use the New Example wizard see Opening distributed examples in the OPL IDE As a hint the fastest way to find this example in the wizard is to choose IBM ILOG OPL examples on the first screen and then on the second screen type warehouse into the field that by default contains type filter text When you do this all other examples are filtered out and you can double click the warehouse example to open it The project The warehouse project opens in the IDE Its contents are shown below with all elements in the OPL Projects Navigator expanded OPL Projects
61. blem 148 scripting changed settings ignored by performance tuning tool 173 Scripting Log output tab writing to 110 scripts debugging 76 execute blocks 92 execute IBM ILOG Script block 110 executing 83 111 112 flow control 80 TUTORIALS postprocessing 106 preprocessing 95 stepping into a loop 102 using a function 97 value of the last expression in Scripting Log page 84 write to Scripting Log 110 semi colon optional mandatory 82 set covering problem 106 sets in oil database example 53 in oil sheet example 67 SheetConnection OPL keyword 69 SheetRead OPL keyword 69 SheetWrite OPL keyword 70 slow model elements 139 146 solution pool filters 163 populating 161 setting options 162 tutorial 156 solutions feasible postprocessing 112 notification 24 obtaining more MIP 161 progress chart 19 35 sorting order in Profiler table 143 sparsity and data initialization 94 in the transportation example 92 spreadsheets connecting to oil sheet example 64 multiple 69 read only file 71 reading from 63 viewing the data 65 viewing the result of an update 73 writing to 63 70 SQL requests knowing the syntax 45 syntax of placeholders 56 stars in Engine Log output tab 20 statements in IBM ILOG Script for OPL 78 states running 18 Statistics output tab progress chart 19 35 steel mill example 36 status after main script 84 status indicator green 24 89 IBM ILOG orange 18
62. cede reete Ree Ene gids ae ete ee 162 Filtering the sol tiorpool z 3 tio ote hintaan b p i nian tetera hte 163 Solution pool fillers ausit ean edt i ht elo dat eda reete 164 Adding a range fi tGr 1 nie ER RU ERR AERE ADIRE UR Mia aSa 165 Flow control script and solution pool enne nnne nnne nennen 167 How the flow control script works sssesseeeeeenneneneen meer nnne nennen nennen 168 Executing the flow control script eeeeeeee nennen nnne einen sen rnnt nente nene 169 Using the performance tuning tool eeeeeeseeeeeeer eene eene nnne nnn nnn nnns 171 Purpose and prerequisites 2 crie Dreier dee nete epe Ata enel nat Renee necp eeu dot scu o tva d 172 Flow perforrmiance TUNING WORKS o cer tne chim tct teneret e teet ue t cepe Se Pace ep ete caedes 173 How to use performance tuning in the IDE nennen nnns 175 Tuning without fixed settings iei nete Hed Re teen Ce RECEN IRE Ee RR Renee aeai 176 Haesults 2 o eoi RICE ei HB die 179 IBM ILOG OPL IDE TUTORIALS 5 6 Tuning with fixed settings ect rente terre catt trie tei ad eee ite fe tits 180 MI IsMeoi M eR 181 Temporary TUNING TES a t teet RR CUR OAM SO eR eee ciii enis 183 M 185 BM ILOG OPL IDE TUTORIALS IDE Tutorials A collection of tutorials that use examples fro
63. ch see Examining the extraction and search information Where to find the files The profiler example is supplied as the model profiler mod included in the profiler project at the following location ILOG OPL IDE TUTORIALS lt OPL_dir gt examples opl profiler The scalable warehouse example is a run configuration of the warehouse project at the following location lt OPL_dir gt examples opl warehouse where lt OPL_dir gt is your installation directory Note You will open this OPL project and all projects in these tutorials using the New Example wizard which allows you to open and work with a copy of the distributed example leaving the original example in place If you need a reminder of how to use the New Example wizard see Opening distributed examples in the OPL IDE IBM ILOG OPL IDE TUTORIALS 137 138 BM ILOG OPL IDE TUTORIALS Identifying slow and memory consuming model elements The information displayed in the table of the Profiler enables you to identify slow or memory consuming elements during execution of the profiler model and possibly to infer what changes in your model might improve execution performance This part of the tutorial uses the profiler example to demonstrate this In this section Presenting the profiler example Discusses the model profiler mod Executing the profiler model Explains how to obtain profiling information Description of the profiling information Describes the informa
64. d at the end of the tuning process Tuning with fixed settings How to tune parameters to get the best performance in a specific context Tuning options To set the level of information reported by the tuning process Temporary tuning files Temporary files created by the tuning process can be saved to disk to examine later IBM ILOG OPL IDE TUTORIALS 175 Tuning without fixed settings To observe this 1 Right click on the warehouse project and select Tune project D The tuning wizard opens 176 IBM ILOG OPL IDE TUTORIALS Tuning wizard E ES Choose tuning parameter Ao Select the run configurations to tune le Basic Configuration le Scalable data Fi le Solution pool script le Filter script Fixed settings Mone Result File WE warehouse warehouse result ops Cancel Tuning wizard By default all the run configurations defined in the project are selected Uncheck the ones you don t want to tune If all run configurations are unchecked the Finish button is not available IBM ILOG OPL IDE TUTORIALS 177 2 In this exercise uncheck all configurations except Scalable data 3 In the Result file area you need to provide a name for the settings file ops output 4 Click Finish During the tuning process the Engine Log reports the percentage of progress the settings worked on at each solve iteration the execution time the objective value the best bound value Time limit exceeded
65. d the blue arrow in the margin moves to the next line which is the statement for warm start var basis new IloOplCplexBasis as shown below iij mulprod_main mod 2 58main 59 var status 0 60 thisOplModel generate B l 62 var produce thisOplModel 63 var capFlour produce Capacity flour 64 65 var best e 66 var curr Infinity gt 67 var basis new IloOplCplexBasis 68 var ofile new IloOplOutputFile mulprod main txt Step by step execution of a script By repeatedly clicking the Step Over button you can follow the execution of the loop one instruction after another would give the same behavior as Step Over in this script because there are no functions so it just executes the current instruction Continuing without stepping At any moment while you are stepping in the script you can ask the IDE to continue executing until completion by clicking the Resume button in the toolbar of the Debug view The IDE executes the rest of the script without stopping at instructions The possible outputs of the script are printed in the Scripting log Aborting execution At any moment while you are stepping in the script you can abort execution Click the Abort the current solve button in the execution toolbar of the main window You can also click the Terminate button in the toolbar of the Debug view The Debug view shows that the status of the execution is termina
66. devex sing devex sing devex sing devex Using devex Using devex Using devex sing devex Iteration loa Engine Log mulprod main mod The last two objective values in the set of solutions are the same and so solving stops ILOG OPL IDE TUTORIALS Debugging a flow control script You are now going to learn how to debug a script The debug features in the IDE are breakpoint management call stack display variable object examination and stepping A simple debugging scenario is to place a breakpoint in a script execute the script by means ofthe Debug button examine the call stack and then interactively execute statements using the Step Over button This section covers the successive debugging steps Adding a breakpoint to a flow control script Examining the flow control call stack Stepping to the next instruction Aborting execution Continuing without stepping Ending execution Adding a breakpoint to a flow control script Still using the Solve models sequence by changing data run configuration of the mulprod model you are going to add a breakpoint to set the debugging mode then execute the script again using this time the Debug button 1 Ifitis not already open double click the mulprod main mod file in the editing area and scroll down to this line just before the loop Ver curr Infinity 2 Right click in the grey margin to the left of this line From the popup menu select To
67. e in which case the demand for this type increases by ten barrels for every dollar spent What you are going to do With this example you will learn how to establish a connection to a database from the IDE read database tables into OPL sets create a new relational table in a database from the IDE write an OPL tuple set to a database by inserting the tuples as new rows in a table Where to find the files For this example you will use the following files oil project the oil blending example in which one run configuration uses an ODBC connection to a Microsoft amp Access database where there is data for a linear programming LP problem oilDB mdb the Microsoft Access database that contains the data for the oil database example You can find the files in the oi1 folder lt OPL_dir gt examples opl oil where lt OPL_dir gt is your installation directory Note You will open this OPL project and all projects in these tutorials using the New Example wizard which allows you to open and work with a copy of the distributed example ILOG OPL IDE TUTORIALS leaving the original example in place If you need a reminder of how to use the New Example wizard see Opening distributed examples in the OPL IDE IBM ILOG OPL IDE TUTORIALS 49 The oil database tables 50 B M The data for the Oil example is stored in the following relational tables GasData OilData Result If you have Microsoft
68. e Stores The capacity values and transportation cost values are internal data that is they are calculated in the model file as shown below Internal data in scalableWarehouse mod int Capacity w in Warehouses NbStores div NbWarehouses w NbStores div NbWarehouses int SupplyCost s in Stores w in Warehouses JEN Ea E I0 UE MES RHENO Ue Note 1 When there is no separate data file all the variables must be initialized in the model file there cannot be statements of the form lob yar er 2 The scalable warehouse model has been artificially increased in size so that the search is long enough for you to interrupt and look at feasible solutions that are not the best with respect to the objective The resulting size is greater than the size allowed in trial mode You therefore need a full copy of OPL to run this example Note the use of the integer division operator div in the capacity calculation and the modulus operator mod The matrix supply s w represents the amount of the product delivered to store s from warehouse w The total delivered to a store could be represented by a very large integer value Instead it is normalized to 1 so that each supply s w value is a proportion of 1 with a floating point value Thus one warehouse could deliver 0 5 half the total for that store another 0 2 a fifth of the total for that store and so on ILOG OPL IDE TUTORIALS You are now going to execute the run configura
69. e and memory consumption the Profiler table displays the extraction and solving phases of the model execution This part of the tutorial uses the scalable configuration of the warehouse example to demonstrate this In this section Presenting the scalable run configuration Discusses the model scalableWarehouse mod Executing the scalable run configuration Explains how to modify the default run configuration Examining the extraction and search information After execution of the model Turning off the Profiler To save execution time and memory Drawing conclusions Contains some recommendations for improving your model IBM ILOG OPL IDE TUTORIALS 147 Presenting the scalable run configuration The warehouse location model is described in detail in Warehouse location problems in the Samples manual It includes a run configuration Scalable data defined by the model scalableWarehouse mod supplied with the warehouse project at the following location lt OPL_dir gt examples opl warehouse where lt OPL_dir gt is your installation directory There is no data file in that configuration The scalable data is declared in the scalableWarehouse mod model as shown in Model of the scalableWarehouse example scalableWarehouse mod Use the File New Example menu command to open the warehouse example The IDE displays the project in the OPL Projects Navigator Open the model in the editing area Model of the scalableWarehouse exam
70. e connections to databases Connecting to the database from OPL The connection is established to an Access database by the following statement in oilDB dat DBConnection db access oilDB mdb The string passed as first argument indicates that you want to connect to an Access database The string passed as second argument designates the Access database file This is a helper implementation actually based on ODBC and you do not need to specify the full path name Path names are resolved relatively to the directory of the current dat file Reading from the database Reading database columns You can read columns from any table into an OPL set using the DBRead statement as shown in oilDB dat Reading database columns to an OPL set oilDB dat Gasolines from DBRead db SELECT name FROM GasData Oils from DBRead db SELECT name FROM OilData IBM ILOG OPL IDE TUTORIALS 55 56 B M You can also read from any table into a tuple and its indexing set as shown in the data file oilDB2 dat Reading database columns to a tuple array oilDB2 dat Gasolines Gas from DBRead db SELECT name name demand price octane lead FROM GasData Oils Oil from DBRead db SELECT name name capacity price octane lead FROM DibDatat ie Reading database columns to a tuple array 0i1DB2 dat is more efficient than Reading database columns to an OPL set oilDB dat because the code is shorter data is not duplicated Reading dat
71. e model by writing an execute IBM ILOG Script block For an example see Changing CP parameters in the Language User s Manual For example you can change the verbosity of the log displayed in the Engine Log tab of the Output window To set a CP parameter in the IDE 1 Create a settings file for the stee1mi11 project by choosing File gt New gt Settings from the main menu In the popup window type steelmill ops as the name of the settings file and click Finish 2 Drag and drop the steelmill ops settings file into the Basic Configuration run configuration See also Adding a settings file in Getting Started with the IDE 3 In the settings file displayed in the IDE editor click Constraint Programming Search control Log control 4 Select Quiet from the Log verbosity drop down list see Setting the Engine Log verbosity steelmil ops ypeparameter description fter 4 Logverbosty TT amp 8 amp Mathematical programming amp Constraint Programming Log period 1000 JE Propagation Control amp amp Search Control General Tolerances Limits Log Control amp amp Language General Run Setting the Engine Log verbosity n iij ij 2 5 Execute the Basic Configuration for the project The Engine Log tab is empty This is the result of the Quiet setting You can now close the route and steelmill projects in the OPL IDE see Closing projects in IDE Reference f
72. e model file in the project The oil database data file Describes the data file in the project Executing the oil database example Execute the example and examine the result in the OPL IDE Viewing the result in the database How to display the Result table after execution using Microsoft Access The Result table after execution Shows the modified Result table after execution IBM ILOG OPL IDE TUTORIALS 47 Description of the example 48 B M Make sure you have read the section Using data sources before you start The oil database example is a linear programming LP problem delivered as a run configuration of the oil project with the supplied database oilDB mdb In this example the data is stored in tables in a relational database This data reflects an optimization problem described in A blending problem in the Language User s Manual Here is a summary the problem An oil company manufactures different types of gasoline by blending different types of crude oil Each type of gasoline must satisfy quality criteria with respect to its lead content and octane rating The company must satisfy customer demand which is 3 000 barrels a day of super 2 000 of regular and 1 000 of diesel It can purchase up to 5 000 barrels of each type of crude oil a day and process at most 14 000 barrels a day It costs four dollars to transform a barrel of oil into a barrel of gasoline The company has the option of advertising a type of gasolin
73. e tables ete iere dte et fe eee Ri eite eid Gade 50 The oil database ptroJect tme e EUR er Ep E idan a ERR SS Ea aE eaa 53 Thie oll database data flle eoe edet deed ete iere tenere die eee te ere 55 Executing the oil database example seeeeeeseeseseeeeeeee eeiam nennen nnne nnne 58 Viewing the result in the database cescccceescceeseeceeeseeeneseneeeseneeseseneneseaeeeneneeeseeneneneneeseneeeessenenes 60 The Result table after execution uesesssesseeeeeeeeeeee entente entren nnne nnt nennt nennen nnns 61 Thi oil sheet example Ee eL te vitae re te dee ee 63 Description of the example lseeeeseeeeseeeesee esee enn tete entente nnns annee nennen nennen 64 The oil data spreadsflieet eee Eee eie ende EMI CR ERE Det v pe kx n Me teal epee estan 65 Anmelden PEE 67 The oilsheet data TIlg eiii ioc eet mete a ret iai ln cd ded 69 Executing the oil sheet example 5 eia eee Pea eR RARE REUS MOERS Rak aire 71 Viewing the result in the spreadsheet enne 73 The RESULT sheet after execution sssesssessssssseesseseene enne nnne nennen nnne nnne 74 Using IBM ILOG Script for OPL eeeeeeeeeeesseieeeeeeeeseeen nnne nn nenne tnnt nnne nnn nnmnnn nnna 75 Purpose and Prerequisites oio eee dene e donee se NE EEE E de Y dE ulace de cedat 76 Features of IBM IEOG Script
74. e with capFlour capFlour if cplex solve curr cplex getObjValue writeln writeln OBJECTIVE curr ofile writeln Objective with capFlour capFlot else writeln No solution break Oy Ue Co b K fey co oo i 3 e oo e Jo J ON Bm w Nhe D N O n D Q DONN C iu un isi Jii A breakpoint before the loop of the script mulprod main mod Examining the flow control call stack The call stack is now spread over two views the Debug view representing the call stack showing nested function calls and the Variable view showing the content of the selected call frame 1 The call stack appears in the Debug view Each function called has information in a stack frame In this example there is one frame mulprod main mod 58 Click the and sign as necessary to expand or collapse nodes cj OPL Projects Debug amp 3 eo 0 ew LRI Eli mulprod_main mod o lt terminated gt mulprod Solve models sequence by changing data OPL Run Configuration 58main E f terminated OPL mulprod Solve models sequence by changing data 59 var status 0 mulprod Solve models sequence by changing data OPL Run Configuration 60 thisOplModel generate amp 58 OPL mulprod Solve models sequence by changing data 61 amp a postProcessing mulprod_main mod suspended at breakpoint 62 var produce thisOplModel var capFlour produce Capa mulprod_m
75. e wizard see Opening distributed examples in the OPL IDE IBM ILOG OPL IDE TUTORIALS 107 Setting up the covering model and data To start working with this example 1 Use the File gt New gt Example menu command to open the covering example The IDE displays the covering project in the OPL Projects Navigator 2 Open the covering mod model file in the editing area Scroll to the DISPLAY postprocessing script in the execute block just after the objective mulprod main mod transp4 mod int NbWorkers range Workers 1 NbWorkers string Tasks int Qualified Tasks assert forall t in Tasks i in Qualified t i in asSet Workers alternate formulation assert forall t in Tasks card Qualified t inter asSet Workers card Qualified t int Cost Workers dvar boolean Hire Workers minimize sum c in Workers Cost c Hire c subject to forall j in Tasks ctr sum c in Qualified j Hire c gt 1 int Crew c c in Workers Hire c execute DISPLAY writeln Crew Crew Postprocessing script covering mod 3 Open the covering dat file The data is initialized in the data file Notice that 32 workers are available The covering data covering dat NbWorkers 32 Tasks masonry carpentry plumbing ceiling electricity heating insulation roofing painting windows facade garden 108 IBM ILOG OPL IDE TUTORIALS garage Qualified
76. ead tuple oilType string name float capacity float price float octane float lead These tuple definitions closely follow the structure of the rows in the GasData and OilData tables respectively of the database You will notice the type concordance between the table columns and the OPL fields The column name in each table contains character strings so the field name in each tuple is of type string the column lead in each table contains floating point values so the field lead in each tuple is of type float Note Some columns that appear to store integer values need to be mapped to OPL fields of type float rather than of type int This is to avoid integer arithmetic or if you are IBM ILOG OPL IDE TUTORIALS 53 54 B M using an Access database source because the numeric values manipulated in Access are of type float Tuple sets and arrays in the model The rows in the Access GasData and OilData tables are first mapped to sets of tuples gasData and oilData in OPL Tuple sets oilDB mod gasType GasData oilType OilData i Note OPL supports sets of tuples as well as sets of int float and string values The tuple sets are then preprocessed using generic indexed arrays see Initializing Arrays in the Language User s Manual to obtain one dimensional arrays gas and oi1 in OPL Tuple sets preprocessed as generic indexed arrays oilDB mod gasType Gas Gasolines g name g g
77. educed MIP has 250 rows 10050 columns and 20050 nonzeros Reduced MIP has 50 binaries 0 generals 0 SOSs and 0 indicators Presolve time 0 18 sec IMIP emphasis balance optimality and feasibility IMIP search method dynamic search Parallel mode none using 1 thread Root relaxation solution time 0 03 sec Nodes Cuts Node Left Objective IInf Best Integer Best Node ItCnt Gap 0 0 1438 1429 18 1438 1429 488 I 0 0 1530 0000 1438 1429 488 6 00 0 0 1438 1429 9 1530 0000 Cuts 24 505 6 00 Engine log for the warehouse example scalable warehouse mod When CPLEX optimizes mixed integer programs it builds a tree with the linear relaxation of the original MIP at the root and subproblems to optimize at the nodes of the tree CPLEX reports its progress in optimizing the original problem in a node log file as it traverses this tree You control how information in the log file is recorded and displayed through two CPLEX parameters The MIPDisplay parameter controls the general nature of the output that goes to the node log The MIP node log interval parameter MIPInterval controls how frequently node log lines are printed Its default value is 100 These parameters can be set in the OPL settings file See Changing a CPLEX parameter value The values for these parameters are also given in CPLEX parameters and OPL parameters CPLEX records a line in the node log for every node with an integer solution if the parameter c
78. en if the run configurations use the same model the tuning process always passes different sav files to CPLEX because the data may be different from one configuration to the next It ignores any change to the default settings specified in execute script statements If you want it to define some CPLEX parameters that should remain unchanged you must pass them as a specific ops file known as the Fixed Settings file The tuning process executes the models several times in the background each time with a different set of settings which may affect the solving time If there is a main block tuning won t work At the end of the solve iterations the process generates an ops file containing the OPL settings CPLEX parameters that it has found to be the best to solve the problem the fastest This tutorial focuses on the IDE implementation but the performance tuning feature also works from the oplrun command See the document oplrun Command Line Interface For a more complete description of the tuning process please refer to the CPLEX documentation IBM ILOG OPL IDE TUTORIALS 173 174 BM ILOG OPL IDE TUTORIALS How to use performance tuning in the IDE Two ways of using the performance tuning tool first without fixed settings then by specifying the settings you want to use In this section Tuning without fixed settings Provides a procedure for tuning a model in the OPL IDE Results Discusses the new settings file create
79. es and nurse teams A good schedule is an optimal one that is a schedule that meets as many of the hospital s overall goals as possible If some of these goals prove incompatible then the solution consists in nevertheless finding a schedule that will work out in other words a feasible schedule The goals include staffing each hospital department with the proper number of nurses at all times matching a nurse s skills such as a Board Certification in Cardiac Care with the requirements of the department establishing a minimum and maximum number of hours worked per week maximizing fairness in how nurses are allocated to shifts that is making sure that no nurses are scheduled for 50 hours a week when others are scheduled for only 25 hours incorporating best practice guidelines such as trying to schedule nurses with compatible skills or with a proven history of working well together on the same team taking into account individual nurse preferences for days off as much as possible keeping salary costs to a reasonable level Sometimes several of these goals will conflict for example during a week when many nurses are on vacation In such a case the solving engine finds no solution As this is not acceptable because a hospital needs a nurse schedule you have to make choices prioritize the goals and relax some constraints accordingly You will see in this tutorial how the IDE guides you through this task Wha
80. eseseeeeeseeeres 112 Relaxing infeasible models eeeeeeeeesieee eese nnne nennen nnne nnn anne nnn innen 115 Presenting the nurse scheduling example seen enne nnne 116 IBM ILOG OPL IDE TUTORIALS Setting up the nurses model and data ssessssssssssessesseeene enne nnne enne nennen nnne nnne nennen 118 Executing the nurses project 1 uci e mee cedente quite d inedit ite etia ae 119 Working on the execution results cececcecsseeeeeseeceseeceeecseneeenenceseeeeeesseeenesenseneseeeeseeeeseseeeneseneeseseeesenenenss 123 Studying the suggested relaxation essesssessssssesseeeeeeeeenne nnne nnne nnne nnne nnne 124 Studying the suggested conflicts nennen nennen nennen 125 Changing the dala trc e ve e e cv e et 126 Executing the nurses project 2 rte ierit te ot o dbi oe true nee de Kaa Ea Raa Rp oe te ete 128 How relaxation and conflict search works sssseeeeeeeeeneen nee nnne nennen 131 Relaxation S eoo Oates tacto dio Se aeter 132 Setting the relaxation level 3 iie RERO ERR ER GREG EORR MEME Mane ara da 133 ernulursc PELIS MI EA Rts 134 Profiling the execution of a model eese nnn 135 Purpose and prerequisites eeeeseieeeisieeeeseseee estne A nrbe EEEE EE nne e nrbes E Ea 136 Identifying slow and memory consuming model elements eee 1
81. f branches 166 Number of fails 35 0 5 Objective 0 2 45 246 2 47 248 2 49 25 2512825222253 0 54 Time seconds Statistics for the steel mill example default CP settings Pausing search You can pause the CP Optimizer search explore the current feasible solution if any in the Problem Browser and then continue the search This is not meaningful in the steel mill example however as the solution is found very quickly Progress chart The progress chart shows all the feasible solutions and the final one Again the progress chart is not particularly interesting for the steel mill example because the optimal solution is found immediately See the progress chart of the route problem in The progress chart CP models for comparison TUTORIALS The progress chart CP models If you execute a constraint programming model solved with the CP Optimizer engine the progress chart is slightly different from the progress chart of CPLEX models To observe it you are going to open the route project 1 Use the File gt New gt Example menu command to open the Call route example The route project will appear in the OPL Projects navigator 2 To run the model open Run Configurations right click on Basic Configuration and select Run this from the popup menu to execute the run configuration 3 Click the Statistics tab Statistics lt 3 f Profiler Objective Solution 8 Proven solution 50000 0 4 0 6 0 8 1 1
82. f the MIPInterval parameter is set to 10 time and memory information appears either every 20 nodes or ten times the MIP interval parameter whichever is greater CPLEX prints an additional summary line in the log if optimization stops before it is complete This summary line shows the best MIP bound that is the best objective value among all the remaining node subproblems IBM ILOG OPL IDE TUTORIALS 23 Examining the results and the data 24 B M After model execution the results are displayed in the Solutions tab and the data structure is displayed in the Problem browser The results If you scroll down through the Solutions tab you see the results for the Open and Supply variables The Open array specifies which warehouses are open The Supply matrix specifies which stores are supplied by which open warehouses 2 Problems E Scripting log Solutions 3 gt Z Conflicts Relaxations Engine log statistics 5 Profiler solution integer optimal tolerance Open 11111111111101 L101011110171191100415271700112101198 011 oo 000000000000000000000000000000 000000000000001 D000000000000000000000000000000 0000000000000000001 DO000000000000000000000000000010 000000000000000000 0 0000000000000000000000000000000 0000000010000000000m0 000000000000000000000000000000 000000001000000000 0 foo000000000000000000000000000000 000000001000000000 0 0 1 0 0 The data structure
83. fferent data Right click the configuration Scalable data and select Set as Default 4 Right click on Scalable data and select Run this to execute the run configuration The Solutions tab displays the optimal solution The other feasible solutions are summarized in the solution pool in the Problem Browser IBM ILOG OPL IDE TUTORIALS 159 160 B M 96 Breakpoints 697 Variables Pool solution 4 with objective 1490 Solution with objective 1480 Pool solution 0 with objective 10470 Pool solution 1 with objective 1530 Pool solution 2 with objective 1520 Pool solution 3 with objective 1510 E SupplyCost 12 22 32 42 52 62 72 82 92 2 12 22 Warehouses 1 50 Decision variables 2 E Open 1111111111110111011 Qo Supply 0o000000000000000000 E Decision expressions 2 TotalFixedCost 360 TotalSupplyCost 1130 XY constraints 2 G ctOpen sum s in 1 200 Supply s 1 lt B ctStoreHasOneWarehouse X sumtw in 1 50 Supply 1 w oo Post processing data Property Solution pool in the Problem Browser scalableWarehouse mod The solutions in the pool are identified by an index number starting from 0 zero Generally the lowest index numbers are for the solutions found earliest The index numbers may change after re populating the pool depending on the strategy in use when the pool reaches its size limit When you select a solution from the list in the Problem Browser the value
84. for OPL aita ies ots ea hate dete opes e c bees 78 The multiperiod production planning example sse nennen nnne 79 Presenting the multiperiod production planning example een 80 Setting up the multiperiod production model and data 82 Executing a flow control script 2 retro nia bete ER HR LR RERUM AER Se aka Es 83 Purpose of the flow control script emen eene 84 Debugging a flow control script inini nennen intente nnne nae nitent nnne 85 The transportation example ii 12 irre itte ertet e e Eu Sedi Severe eire 91 Presenting the transportation example sssseeeeeneneenn enne nnne nnne 92 Setting up the transportation model and data ssssssseeeeeeeeneee nennen 94 Executing preprocessing Scripts either id efe recreate deel 95 Purpose of the preprocessing scripts sesssseeeeenn emen nre 96 Debugging a preprocessing script enne rennen nnne nnne 98 Fhe covering example 552 seni ce iere Ure p Lr Ht ini 105 Presenting the covering example ssssseeeenenneen eene nne 106 Setting up the covering model and data nennen nene 108 Purpose of the postprocessing script sesssseeeennen menn 110 Executirig a postprocessing scfIpt cce iis eee ridere tte ti b er nes 111 Postprocessing a feasible SOIUTION ccececeeceeeeeeeseceeeeeeeeeeeeeeseseceneseeeeseeeeeseeeenenens
85. g working with external data 44 constraints in the transportation example 92 labeling 132 Continue button 89 90 104 Copy contents to clipboard right click command from Profiler column headers 142 Count column header in Profiler 150 counting in Profiler table 150 covering sample models 105 106 CP Optimizer working with external data 44 CPLEX engine warm start 88 CPLEX node log 22 185 186 CPLEX parameters for the solution pool 162 ignored by performance tuning tool 173 in the call stack 88 setting a value 26 41 96 CPLEX performance tuning tool 172 cplex model instance predefined object 88 creating a database table 56 data display 97 external 44 initialization and sparsity 94 table view in Problem Browser 24 data files oil database example 55 oil sheet example 69 data sources connecting to 45 table loading 54 data structures in Problem Browser 24 data tables oil database example 50 database connection connectivity 45 data tables 50 model 53 ODBC 55 Oracle 45 prerequisites 45 reading columns and rows from a database 55 storing results in a database 56 supported databases 45 the oil database example 47 updating a database 56 viewing the data tables 50 database table creating 56 DBConnection OPL keyword 45 55 DBExecute OPL keyword 56 DBRead OPL keyword 55 DBUpdate OPL keyword ODBC vs Oracle 56 Debug button 85 98 debugging flow control script 85 preprocessing
86. g Microsoft Excel The RESULT sheet after execution Shows the modified RESULT table after execution IBM ILOG OPL IDE TUTORIALS 63 Description of the example 64 B M Make sure you have read the section Using data sources before you start The oil sheet example is a linear programming LP problem delivered within the oi1 project as a specific run configuration associating the oil mod and oilSheet dat files with the spreadsheet oilSheet x1s In this example the data is stored in sheets of an Excel spreadsheet The optimization problem it reflects is described in A blending problem in the Language User s Manual What you are going to do With this example you will learn how to establish a connection to a Microsoft Excel spreadsheet from the IDE read data from the spreadsheet into OPL arrays write data to the spreadsheet from the IDE Where to find the files For this example you will need to use the following files oil project the oil blending example in which one run configuration uses a connection to an Excel spreadsheet where there is data for a linear programming LP problem oilSheet xls the Excel spreadsheet that contains the data for this run configuration Both files are at the following location lt OPL_dir gt examples opl oil where lt OPL_dir gt is your installation directory Note You will open this OPL project and all projects in these tutorials using the New Example wizard w
87. generated if a particular name of a cut appears then only that kind of cut was generated The column labeled ItCnt records the cumulative iteration count of the algorithm solving the subproblems Until a solution has been found the column labeled Gap is blank If a solution has been found the relative gap value is printed when it is less than 999 99 the value is printed otherwise hyphens are printed The gap is computed as best integer best node objsen abs best integer le 10 Consequently the printed gap value may not always move smoothly In particular there may be sharp improvements whenever a new best integer solution is found Moreover if the populate procedure of the solution pool is invoked the printed gap value may become negative after the optimal solution has been found and proven optimal CPLEX also logs its addition of cuts to a model Cuts generated at intermediate nodes are not logged individually unless they happen to be generated at a node logged for other reasons CPLEX logs the number of applied cuts of all classes at the end CPLEX also indicates in the node log file each instance of a successful application of the node heuristic The denotes an incumbent generated by the heuristic Periodically if the MIP display parameter is 2 or greater CPLEX records the cumulative time spent since the beginning of the current MIP optimization and the amount of memory used by branch amp cut For example i
88. ggle Breakpoint and a blue dot appears in the margin of the editing area to signal the breakpoint Note To remove a breakpoint right click and select again Toggle Breakpoint to make the blue dot disappear You can also double click in the grey margin to set and remove break points IBM ILOG OPL IDE TUTORIALS 85 86 B M 58main 59 var status 0 60 thisOplModel generate var produce thisOplModel var capFlour produce Capacity flour var best var curr Infinitv oggle Breakpoint k lCplexBasis lOutputFile mulprod main txt v Show Quick Diff Ctri Shift Q capFlour capFlour v Show Line Numbers writeln OBJECTIVE curr ofile writeln Objective with capFlour capFlot wo oA oO UI else writeln No solution break co CO J e I Inserting a breakpoint 3 In the main toolbar click the arrow on the Debug button in the toolbar and select 1 mulprod Solve models sequence by changing data to run the script Execution stops at the breakpoint and a blue arrow in the margin shows the current position as shown below ILOG OPL IDE TUTORIALS var status 0 thisOplModel generate var produce thisOplModel var capFlour produce Capacity flour C Oy Oy O var best Sur pdEIDSEYZ var basis new IloOplCplexBasis var ofile new IloOplOutputFile mulprod main txt while 1 best curr writeln Solv
89. he Scalable data configuration with the MIP gt Solution pool options you set you may decide to go further and create arrays of variables and coefficients to add range or diversity filters There are two kinds of filters for the solution pool Diversity filters allow you to generate solutions that are similar to or different from a set of reference values that you specify for a set of binary variables Range filters allow you to generate solutions that obey a new constraint specified as a linear expression within a range See the section about filtering the solution pool in the CPLEX User s Manual for details on how these filters work 164 IBM ILOG OPL IDE TUTORIALS Adding a range filter A range filter adds a constraint over a linear expression You add a range filter if for example you have used the solution pool to get many solutions but you are interested only in the solutions where the number of open warehouses is between 30 and 43 The warehouseCplexFilters mod model has been written for this purpose as a variation of scalableWarehouse mod This model contains the execute block shown in the code extract below Preprocessing script to filter solutions warehouseCplexFilters mod define a range filter applied to solution pools execute var vars new Array var coefs new Array for var w in Warehouses vars w 1 Open w coefs w 1 1 cplex addRangeFilter 30 43 vars coefs With this data in
90. he solution pool in the OPL IDE You will a learn about the default pool of feasible solutions b obtain more non optimal solutions c set some solution pool options 2 Learn about solution filters and add a range filter See Filtering the solution pool 3 Use the IBM ILOG Script API instead of OPL settings See Flow control script and solution pool You will a populate the solution pool and use the solutions b add a range filter to control which solutions are kept in the pool Where to find the files The tutorial is based on the warehouse project available at the following location OPL dir NexamplesVopl warehouse where OPL dir is your installation directory The warehouse location problem is described in Warehouse location problems in the Samples manual Note You will open this OPL project and all projects in these tutorials using the New Example wizard which allows you to open and work with a copy of the distributed example leaving the original example in place If you need a reminder of how to use the New Example wizard see Opening distributed examples in the OPL IDE ILOG OPL IDE TUTORIALS The solution pool in the OPL IDE Explains how the solution pool works how to use it from the IDE Problem Browser and how to set options In this section How the solution pool works For a mixed integer problem MIP that generates multiple solutions Examining pool solutions in the Problem Browser Explains how t
91. hich allows you to open and work with a copy of the distributed example leaving the original example in place If you need a reminder of how to use the New Example wizard see Opening distributed examples in the OPL IDE ILOG OPL IDE TUTORIALS The oil data spreadsheet The data for the oil sheet example is stored in the following sheets gas oil RESULT Provided that you have Microsoft Excel installed on your computer you can view the contents of any of these sheets by simply double clicking the Excel file in Windows Explorer You should view this file in the copy of the project you created when you opened the example using the New Example wizard If you did not change any of the default settings in the New Example wizard that should be in your default workspace at the following location C Documents and Settings lt user gt Application Data ILOG OPL Studio IDE lt version gt oil oilSheet xls Microsoft Excel opens the spreadsheet and you can see the first sheet and the tabs for all the sheets Click a tab to see its contents Notice that the RESULT sheet is initially empty The external data structure for the oil database example and the oil sheet example is the same EJ Microsoft Excel File Edit View Insert Format Tools Data RoboPDF Window Help inl x dd Bava 10 BZU Ez gt A B ua ta 2a as 3 2 zi a ga V Reply with Changes End Review E Hoes D18 v f E oilSheet xls M g
92. how to execute it and debug the preprocessing script The covering example Presents the example and explains how to execute it and debug the postprocessing script IBM ILOG OPL IDE TUTORIALS 75 Purpose and prerequisites 76 B M IBM ILOG OPL enables you to use a scripting language called IBM ILOG Script for OPL This is an implementation of the ECMA 262 standard also known as JavaScript which supports the nonmodeling elements of OPL This tutorial assumes that you know how to work with projects in the IDE If this is not the case read Getting Started with the IDE first Note This section uses several models solved by the CPLEX engine but the features described work in the same way with models solved with the CP Optimizer engine The first section Features of IBM ILOG Script for OPL is a short list of what IBM ILOG Script enables you to write in your OPL projects Then as you go through this tutorial you will become familiar with the following examples each illustrating one way of using IBM ILOG Script for OPL The multiperiod production planning example flow control The transportation example preprocessing The covering example postprocessing More complex examples of scripting are available in lt OPL_dir gt examples opl where lt OPL_dir gt is your installation directory They are used in IBM ILOG Script for OPL in the Language User s Manual For more information see also IBM I
93. ies or both Other company product or service names may be trademarks or service marks of others Acknowledgement The language manuals are based on and include substantial material from The OPL Optimization Programming Language by Pascal Van Hentenryck 1999 Massachusetts Institute of Technology Table of contents DE Pare da erc 7 About IDE tutorial sissi eaaa aA iea a a 9 Understanding solving statistics and progress MP models 11 P rpose ot the TUtOrlal uoce cs crede cre mee Seed eret ene c dre be pet turp ceder dvi eub 13 The scalable warehouse example eese esee eene tnnenn tnnt nnne nnne nnne nente rennen 14 The scalable warehouse proj ct ettari timen ERR RUE ER RR RE CH ERASERR IRAE ERR tRR ERE Redafe 15 Executing the warehouse project with scalable data emen 18 Examining the statistics and progress chart MP ssssssseeeeeneen meme 19 The Progress Chart MP models sssssesseeseseeseeeeeneee nnne nnne nnne rennen nnne 20 The Statistics table MP models nenne enne nnne aai nennen 21 Examinirig the engirie log ce ai rdc te Le ree tet ice pcena ah i d ee ric etr redit eel 22 Examining the results and the data 2 or nile sciet ettet e Cn toi e eer ba vn ce ee A dod 24 Changing a CPLEX parameter value sessssssesssesseseeeeee enne nnne entren nennen rese tnn
94. in Gasolines sum o in Oils Blend o g Gas g demand a g 10 foral g in Gasolines sum o in Oils Oi o lead Gas g lead 1 Blend o g lt 0 sum o in Oils g in Gasolines Blend o g lt 14000 foral g in Gasolines 0 lt sum o in Oils Oi o octane Gas g octane 1 Blend o g s Post processing data 1 Result lt Crude1 Super 2088 9 0 lt Crude1 Regular 2111 1 750 gt 0 Crudel Diese Property Value Problem Browser after execution oilDB mod At the end of execution you see the following message in the Solutions tab E Problems E Scripting log Conficts Relaxations 4 Engine log Statistics Profiler Ee BBC HR solution optimal with objective 287750 Blend 2088 9 2111 1 800 777 78 4222 2 0 133 33 3166 7 2001 a 0 750 0 Solutions tab oilDB mod 58 IBM ILOG OPL IDE TUTORIALS You can examine the data and variables in tabular form from the data structure tree built in the Problem Browser You can also see the table of all the results together in Microsoft Access IBM ILOG OPL IDE TUTORIALS 59 Viewing the result in the database When you have successfully executed the run configuration in the IDE you can view the contents of the newly created table Result in the database 1 Close the IDE and Microsoft Access if it is still open 2 Restart Microsoft Access by double clicking the database file 0i1DB mdb in Windows Explorer
95. intRoute r WEA CEO EEO E UE writeln r e 0 Hes Areas e e d writeln Routes Por qvas tlg Roures 14 printRoute r IBM ILOG OPL IDE TUTORIALS 97 Debugging a preprocessing script 98 B M This section covers the successive debugging steps Adding a breakpoint to a preprocessing script Examining the preprocessing call stack Stepping out of an execute function Stepping into a function Stepping out of a lower level function Monitoring a function in a loop Adding a breakpoint to a preprocessing script You are going to add a breakpoint to set the debugging mode then execute the script again using this time the Debug button To add a breakpoint 1 In the transp4 mod file scroll to the line containing the printRoute function in the DISPLAY execute block function printRoute r 2 Double click in the grey margin to the left of the line A blue dot appears in the margin of the editing area to signal the breakpoint 3 In the main toolbar click the arrow to the right of the Debug button and select 1 transp Even better sparsity to run the script Execution stops at the breakpoint and information appears in the Variables view and the Scripting log ILOG OPL IDE TUTORIALS 58 59execute SETTINGS 60 settings displayComponentName true 61 settings displayWidth 40 62 writeln Routes Routes 63 64 write r p writeln r e o r e d writeln Rou
96. ions section CPLEX parameters and OPL parameters 8 warehouse_tuning ops 3 a Type parameter description filter Tuning information display Display standard minimal reporting v S Mathematical programming General Conflicts Emphasis Feasopt Tuning time limit 10000 Preprocessing Read Simplex Mixed Integer Programming Barrier Network H E Sifting gt Constraint Programming E Language it Tuning measure Average v ii P Tuning repeater 1 uU l E E E H E MP Tune options The possible Tune settings are Tuning information display Specifies the level of information reported by the tuning tool as it works Options are No display 0 Display standard minimal reporting 1 the default Display standard report plus parameter settings 2 Display exhaustive report and log 3 Tuning measure Controls the measure for evaluating progress when a suite of models is being tuned You can specify whether you want the best average performance or the least worst performance across a set of models Options are Average mean time the default Minmax minmax time IBM ILOG OPL IDE TUTORIALS 181 Tuning repeater Specifies the number of times tuning is to be repeated on reordered versions of a given problem Options are Any non negative integer Default 1 Tuning time limit Sets a time limit per model and
97. it to the Basic Configuration In the settings file select Mixed Integer programming gt Solution pool from the tree on the left Check the Populate solution pool box and set the value of Limit on number of solutions kept in pool to 3 Then execute the run configuration The Problem Browser displays only 3 feasible solutions Click the Reset button to restore the Limit on number of solutions kept in pool to its default value then set the Solution pool intensity option to Aggressive and execute again The execution yields many more solutions Note Other parameters may also have an effect on the solution pool just as they affect MIP ILOG optimization or feasibility generally See CPLEX parameters and OPL parameters in Mathematical programming options for more information See also the part dedicated to the solution pool in the CPLEX User s Manual in particular to understand the difference between collecting solutions and populating the pool OPL IDE TUTORIALS Filtering the solution pool Describes how to write filters by means of IBM amp ILOG Script statements In this section Solution pool filters Explains diversity filters and range filters Adding a range filter Also explains how to add a diversity filter IBM ILOG OPL IDE TUTORIALS 163 Solution pool filters You can use IBM Script statements to filter out solutions from the pool If for example you are not satisfied with the solutions yielded by t
98. ization of Values2 E PRE_PROCESSING 0 7188 94 5 394 432 99 0 0000 0 942 904 97 1 11 Ej EXECUTE INIT Valuest 0 2969 3995 1 404 928 26 0 2969 633 458 120 4795 1 4 E INITr 0 0000 0 0 0 0 0000 0 656 0 1 2 INIT n 0 0000 0 0 0 0 0000 0 104 0 1 1 INIT Valuest 0 0000 0 442 368 8 0 0000 0 455 800 4795 1 1 EXECUTE INIT Values2 0 4219 55 3 989 504 73 0 3281 700 456 888 479 1 2 INIT Values2 0 0938 12 569 344 1095 0 0938 200 456 440 4795 1 1 Comparing execution time profiler mod In other words inline initialization of the values2 array is faster than initialization in the script Memory consuming elements If you now examine the Profiler table from the point of view of memory consumption and look at the Local Memory column you can see that initialization of Values2 uses much more memory than initialization of values3 It even increases the Peak Memory EXECUTE INIT Values2 0 4219 55 3 989 504 73 0 3281 700 456 888 4795 1 2 INIT Values2 0 0938 12 569 344 1095 0 0938 200 456 440 4795 1 1 3 EXECUTE INIT Values3 0 0000 0 0 0 0 0000 0 27 768 3 1 4 INIT Yalues3 0 0000 0 0 0 0000 0 27 320 3 1 3 E INIT indexes 0 0000 0 0 0 0 0000 0 25 200 3 1 2 INITT 0 0000 0 0 0 0 0000 0 296 0 1 1 Memory consumption profiler mod This shows the interest of using tuple based indexing when the structure is very sparse LOG OPL IDE TUTORIALS Examining model extraction and solving In addition to tim
99. l then becomes feasible IBM ILOG OPL IDE TUTORIALS 125 Changing the data The list of required assignments is given in the data file nurses dat 0000000000000000000 0000000000000000000000000 0000000000000000000000000 0000000000000000000000000 0000000000000000000000000 0000000000000000000000000 0000000000000000000000000 0000000000000000000000000 0000000000000000000000000 99RequiredAssignments Gb ab at al 100 0 10 104 1 1 1 05 Uo 0 n 07 0000000000000000000 0000000000000000000000000 0000000000000000000000000 0000000000000000000000000 0000000000000000000000000 0000000000000000000000000 0000000000000000000000000 0000000000000000000000000 0000000000000000000000000 99RequiredAssignments Bisbal 100 101 3 4 n 1 1 n V 105 107 In this example it appears that the assignment to relax is the fifth value from the left in the top row 1 Open nurses dat in the Editing Area and scroll to the RequiredAssignments section 2 Change it to 0 to make the model feasible TUTORIALS DE ILOG OPL B M 126 00000000 00000000 oo 0 0 000000000000000000000000 ments 00000000000000000000000000 0000000000000000000000000 0000000000000000000000000 111310000000000000000000000 000000000000000 00000000000000 99RequiredAssiq 100 101 102 103 104 105 0 0 0 TUTORIALS 127
100. lick the run configuration Even better sparsity and choose Run this Note You could also right click Even better sparsity and choose Set as default and then run it by right clicking the project and choosing Run gt Default Run Configuration Upon completion the IDE displays the results in the Scripting log t Problems E Scripting log Solutions Conficts Relaxations 5 Engine log Statistics Profiler Routes lt p bands e lt o GARY d FRA gt gt lt p bands e lt o GARY d DET gt gt lt p bands e lt o GARY d LAN gt gt lt p bands e lt o GARY d WIN gt gt 4 lt p bands e lt o GARY d STL gt gt lt p bands e lt o GARY d FRE gt gt lt p bands e lt o GARY d LAF gt gt lt p bands e lt o CLEV d FRA gt gt lt p bands e lt o CLEV d DET gt gt See What happens when you execute a run configuration in IDE Reference for details of the execution process IBM ILOG OPL IDE TUTORIALS 95 Purpose of the preprocessing scripts 96 B M In this model preprocessing scripts are used for Initializing an array Setting a CPLEX parameter Setting an OPL option Setting the display of variables Initializing an array The recommended syntax to initialize arrays is via generic indexed arrays as shown in the code extract below which sets up a cost array for the routes Generic indexed arrays an ex
101. lprod_main mod model file in the editing area Scroll to the main statement presented here The flow control script mulprod_main mod main Var status 0 thisOplModel generate var produce thisOplModel var capFlour produce Capacity flour var best xar eurr Infinity var basis new IloOplCplexBasis var ofile new IloOplOutputFile mulprod main txt gus C 3D 3 di best curr Note that a semi colon at the end of a line is not mandatory it is used for consistency with the OPL modeling language IBM ILOG Script for OPL does not require a semi colon at the end of a line the OPL modeling language does Double click the mulprod dat file to see the data The production data mulprod dat Products kluski capellini fettucine Jj Resources flour eggs NbPeriods 3 Consumption OI DE OPTAT OPI DIS Nes S A Capactey a 20e 0 es Demand Loli TOO SD T m20920099090 L S0 00 O 1 Ixventonsy L0 91s Invooest Od 0s e Insidetcost 0 4 0 6 0 1 Is Ortesx cle os CE MEO Gra Ome Ore ane ILOG OPL IDE TUTORIALS Executing a flow control script The first run configuration Solve problem once appears as the default Since this not the run configuration that contains the flow control script you will first change the default run configuration To execute the appropriate run configuration 1 Right click Solve models sequence by changing data and select Set as default
102. m the product distribution to illustrate typical features and use cases of the OPL IDE In this section About IDE tutorials Gives the prerequisites for reading this document and outlines the structure Understanding solving statistics and progress MP models Shows how the IDE displays a dynamically updated progress chart for a mixed integer programming MIP example that takes some time to solve Understanding solving statistics and progress CP models Shows how the IDE displays a dynamically updated progress chart for a constraint programming example that takes a few seconds to solve Working with external data Explains how to connect to data sources from OPL based on the example of databases and then provides two practical cases Using IBM ILOG Script for OPL Teaches the features of the IDE for scripts written in IBM ILOG Script for OPL including the script debugging facilities Relaxing infeasible models Uses the nurses example to demonstrate how the IDE detects conflicts and searches for relaxations in models that appear infeasible after execution Copyright IBM Corp 1987 2009 7 Profiling the execution of a model Explains how the IDE Profiler table can help you improve your model to make it run faster while consuming less memory Working with the solution pool Explains how to access a project solution pool in the IDE and how you can set options and define filters on solution pool generation Using the performance
103. mate of the size of the search tree should be smaller after the initial propagation as choices will have been eliminated However this value is always an overestimate of the log of the number of remaining leaf nodes of the tree because it does not take into account the action of propagation of constraints at each node The memory used by the optimizer during the initial propagation is reported Also any parameter change from its default is displayed at the head of the search log In order to interpret the remainder of the log file you may want to think about the search as a binary tree The root of the tree is the starting point in the search for a solution each branch descending from the root represents an alternative choice or decision in the search Each of these branches leads to a node where constraint propagation during search will occur If the branch does not lead to a failure and a solution is not found at a node the node is called a choice point The optimizer can make an additional decision and create two new alternative branches from the current node or it can jump in the tree and search from another node The lines in the next section of the progress log are displayed periodically during the search and describe the state of the search The display frequency of the progress log can be controlled with parameters of the optimizer See Changing a CP parameter value The progress information given in a progress log update includes Br
104. mize thresholds icon Ed at the top right of the Profiler tab to display the sliders The Time threshold and Memory threshold sliders at the top of the Output window enable you to dynamically change the minimum percentage of time or memory above which you want the figures to appear on a blue time or pink memory background Compare Time threshold set to 10 and memory threshold set to 50 profiler mod to Profiling information for the profiler example more time figures are shown against a blue background when the time threshold is set to 1096 and fewer memory figures appear against a pink background when the memory threshold is set to 5096 i Note The figures shown in the illustrations may be different on your machine 144 BM ILOG OPL IDE TUTORIALS 2 Problems E scripting log J Solutions E Conflicts H Relaxations Gr Engine log ley Statistics ES Profiler 55 BI EJ H jae n aatan j Time threshold 10 Memory threshold d I Description Time TENE Peak Memory Peak Memory Self Time Self Time Local Memory Local Memory Count Nodes ROOT 0 7344 10095 5 533 696 10095 0 2812 10095 975 032 10095 1 18 amp LOAD MODEL profiler DEAEA1D8 0 4531 62 1 740 800 31 0 0000 0 944 256 97 1 12 PRE_PROCESSING 0 4531 62 1 736 704 31 0 0000 0 942 904 97 1 ti amp EXECUTE INIT valuesi 0 2500 34 1 085 440 20 0 2344 83 458 120 4795 1 4 EXECUTE INIT Values2 0 1875 26 651 264 1295 0 1250
105. n IBM ILOG OPL IDE TUTORIALS 11 12 B M Changing a CPLEX parameter value Explains how to change a mathematical programming option in the IDE ILOG OPL IDE TUTORIALS Purpose of the tutorial The tutorial assumes that you know how to work with projects in the IDE If this is not the case read Getting Started with the IDE first The tutorial uses a model solved by the CPLEX engine to describe the statistics and progress chart in the IDE output view However statistics and progress chart work in a very similar manner for models solved with the CP Optimizer engine Where slight differences can be observed they are indicated as appropriate Starting from a scalable run configuration of the warehouse example presented in The scalable warehouse example this tutorial covers Executing the warehouse project with scalable data Examining the results and the data Changing a CPLEX parameter value IBM ILOG OPL IDE TUTORIALS 13 The scalable warehouse example 14 B M The scalableWarehouse mod file is a scalable version of the warehouse location model that is described in detail in Warehouse location in the Language User s Manual This section assumes that you are familiar with the integer and Boolean variables used to solve this problem as explained in that document Here is a summary the problem A company is considering a number of locations for building warehouses to supply its existing stores Each possi
106. n or it may contain more Sometimes CPLEX finds a solution that is worse than the current incumbent In this case the worse solution may enter the pool although the incumbent callback is not called Populate is the mode where after the MIP search you explicitly make the choice of finding more solutions by turning on an option that activates a special heuristic by means of a call to the populate method 158 IBM ILOG OPL IDE TUTORIALS Examining pool solutions in the Problem Browser After you execute a run configuration of a MIP problem the information on the solutions found is displayed as follows The Statistics tab displays the number of solutions in the pool The Solutions tab displays the optimal solution If there are pool solutions in the Problem Browser by clicking on a pool solution you display the details of that intermediate feasible solution in the Solution tab The drop down list at the top of the Problem Browser numbers each solution other than the final one and identifies it by its objective value To view pool solutions 1 In the warehouse example right click on Basic Configuration and set it to default if it is not the default This run configuration should contain warehouse mod warehouse dat 2 Right click on Basic Configuration and select Run this You obtain only one solution In the Solutions tab optimal solution with objective 383 3 You decide to see what solutions you get with di
107. nd Relaxations tabs TA nurses ops ype parameter description fiter Error imit so EG 6 Mathematical programming m S Constraint Programming xn i 2 ELE 5 6 Language Postprocess feasible solutions Aa General A im zm Display solution Iv R Display relaxations vi A Display conflicts M B RI Collect profiling information v zm crore og EE Export format No export E R Relaxations and conflicts checked by default 3 Right click on the nurses project and select Run Basic configuration After a few seconds the Conflicts and Relaxations tabs indicate where the relaxations and conflicts are as shown in the following screen shots When a conflict or relaxation is selected in either the Conflicts and Relaxations tabs the corresponding code is highlighted in the model IBM ILOG OPL IDE TUTORIALS 119 3 2 amp 5 two shifts in the same time are incompatile 4 forall s in Shifts sum s2 in Shifts incompatShifts s s2 1 NurseAssignments n s2 lt 1 respect required assignments n mec gnm global max worked tim forall n in Nurses ctNurseMaxTimeConstraints NurseWorkTime n lt MaxWorkTime Nurse Nurse incompatibility forall lt ni n2 gt in NurseIncompat s in Shif ctNurseIncompatConstraints NurseAssignments n1 s NurseAssignments rg Displaying conflicts for nurses mod 1200 IBM ILOG OPL IDE TUTORIALS
108. ng results To observe how tuning results differ if you pass a file of fixed settings 1 2 Select the warehouse project Add a new settings file as explained in Adding a settings file in Getting Started with the IDE to the Scalable data configuration In the Mixed Integer Programming gt Tolerances page change the Relative MIP gap tolerance to 0 02 Right click on the warehouse project and select Tune project D 5 Make sure that only the run configuration Scalable data is selected 6 Inthe Fixed settings field select the name of the ops file you have just created with a custom value for Relative MIP gap tolerance 7T Change the name of the tuning result file so as not to overwrite the existing one 8 Click Finish ILOG The Relative MIP gap tolerance value you have set appears in the tuning results Note Please note that the progress of the tuning operation is shown in two different locations in the Engine Log tab and at the right of the IDE s Status Bar The percentages shown in these two locations may not be identical OPL IDE TUTORIALS Tuning options The Mathematical programming gt Tune options enable you to set the level of information reported by the tuning process the measure for evaluating the progress the number of times the process should be repeated on perturbed versions and the time limit per run configuration and test set These options are documented in Mathematical programming opt
109. ng the multiperiod production planning example you will open the mulprod example and discover its flow control script see Setting up the multiperiod production model and data run the model see Executing a flow control script debug the script as explained in Debugging a flow control script that is add a breakpoint examine the call stack step to the next instruction abort execution or continue execution to the end of the script Where to find the files To do so you will work mainly with the run configuration Solve models sequence by changing data which associates the files mulprod main mod and mulprod dat of the mulprod project available at the following location OPL dir Nexamples V oplWMmulprod ILOG OPL IDE TUTORIALS where lt OPL_dir gt is your installation directory Note You will open this OPL project and all projects in these tutorials using the New Example wizard which allows you to open and work with a copy of the distributed example leaving the original example in place If you need a reminder of how to use the New Example wizard see Opening distributed examples in the OPL IDE IBM ILOG OPL IDE TUTORIALS 81 Setting up the multiperiod production model and data 82 B M To start working with this example 1 Use the File gt New gt Example menu command to open the mulprod example The IDE displays the mulprod project in the OPL Projects Navigator 2 Open the mu
110. nn nenin 26 Understanding solving statistics and progress CP models 29 Purpose of the tutorial eee ite IRR L Re e Lacs DTE E e eee dee He Rc Ec eL ie euge 30 FEhie steel mill example 2411 roD E eR E ee e ep e dete E eon 31 Executing the model in the OPL IDE i utet aide ais certe E viel te ex pee Sr eg bete cedens 32 Coloring of CP keywords and functions in the IDE sssssseseseeeneeneeeneennen nnnm eene 33 Examining the statistics and progress chart CP essent 35 SIaltiStiCS 5 sated cie emere eet tents EE E A a d plo a er i eti d 36 The progress chart GP rmodels 1 erac t RE D e iud 37 Th statistics table GP models tree PUR OR ae Eae p MRNA 38 Examining the engine log eter hase eva tke ea edm icity kae denne ie cO de Ye dee pre cede Eyed 39 Copyright IBM Corp 1987 2009 3 Changing a CP parameter Value 35 tate erect teet cera ete eerie trien reeds 41 Working with external data 1eeeeeeeeeeeee esee enne eene nnnnn nnne nent r nannten nns 43 Purpose ANG prerequisites retener ETET 44 USING data SOUNCESs nato ne E ERG HERR EI Re EC e BEC gauccataaddenatvalaaeesccvevaad ssbesarehaccdenadseiear 45 The oil database example iiit dett ec S Eee ee ee A ecce 47 Description of the example 5 nets EAE eere ee ee eed ode ace ER eee 48 The oili databas
111. nts n s 1 This means that the equality to 1 would no longer be mandatory in the relaxed model The constraint itself seems correctly expressed Practically it means that a feasible solution can be found and hence a schedule can be worked out if Anne is not necessarily assigned to Consultation on Monday from 8 to 12 In other words changing this data is sufficient for the model to be feasible see Changing the data Important Be aware however that infeasibility may be the consequence of an error in the modeling of another constraint Let us now take another view at infeasibility by Studying the suggested conflicts ILOG OPL IDE TUTORIALS Studying the suggested conflicts When a model is proved infeasible OPL also searches possible conflicts between the constraints of the model A conflict is a set of constraints that cannot be all true at the same time At least one of them must be removed or modified to avoid the conflict See How relaxation and conflict search works for more information Return to the Conflicts tab if necessary For the nurses example the IDE displays the proposed conflict in the Conflicts tab The conflict is that Anne cannot be assigned simultaneously to both the Emergency and the Consultation shifts In other words to avoid this particular conflict one of the required shifts that is one of the constraints on assignments to shifts must be removed If no other conflicts exist in the model the mode
112. o change the default run configuration and analyze the result after a new run Obtaining more solutions Explains how to set CPLEX parameters to obtain additional feasible solutions Seiting solution pool options To change the gap tolerance the number of solutions stored and the criteria on which solutions are substituted for others when the pool has reached its maximal capacity IBM ILOG OPL IDE TUTORIALS 157 How the solution pool works The solution pool feature allows you to generate and store multiple solutions to a mixed integer programming MIP model This feature uses an extension of the CPLEX branch and cut algorithm to generate multiple solutions in addition to the optimal solution If your model expresses a mixed integer problem MIP and generates intermediate feasible solutions the OPL IDE displays the pool of solutions obtained after execution at the top of the Problem Browser see Solution pool in the Problem Browser scalableWarehouse mod You can set a number of options CPLEX parameters to change how the pool is populated There are two ways to collect pool solutions the default accumulation of feasible solutions over the incumbent and the explicit choice of populating the pool according to default or custom settings In the default mode any feasible solution found during the regular search by the MIP optimization algorithm is listed as a pool solution The solution pool may contain only the incumbent solutio
113. on and the solving strategy as described in A blending problem in the Language User s Manual 44 IBM ILOG OPL IDE TUTORIALS Using data sources Databases supported IBM ILOG OPL interfaces with some of the RDBMS supported by IBM ILOG DBLink For a list of the databases supported by OPL see Supported databases in Working Environment Connection prerequisites If you are working with Oracle As for most database management systems you must have a user account and a password allowing you to connect to an existing database The Oracle client must be installed or accessible through the network Ifyou are working with ODBC having Microsoft Access installed will allow you to view the contents of the tables in the database However you do not have to install this product on your computer In order to follow the interactions with the database some knowledge of the syntax of the query language SQL is useful Connection to a database The OPL keyword DBConnection establishes a connection to a database It requires two arguments the database client you want to use and the connection string The first argument is a string indicating the name of a database system known to IBM ILOG DBLink which is a value such as oracle9 Note Before using a database connection you must make sure that the corresponding database client is correctly installed on your system The connection string passed as second argument must
114. on null values exist only when i is equal to 2 j The values are then i In the supplied example i and j range from 1 to 300 This range makes the execution run in an acceptable amount of time on an average laptop computer Still the model is not too small so that differences in modeling significantly affect execution time and memory consumption You can change the value of the upper range limit n to adjust the execution time if it is too fast or too slow on your own machine ILOG OPL IDE TUTORIALS Executing the profiler model To execute the model and display the Profiler table 1 Right click on the profile project and select Run gt Basic Configuration If necessary see Executing a project in Getting Started with the IDE for a reminder of the execution process The model solves with no error message 2 Click the Profiler tab to display profiling information Next read the Description of the profiling information IBM ILOG OPL IDE TUTORIALS 141 Description of the profiling information When execution stops the information collected about execution time memory consumption and model extraction is organized in tabular form in the Profiler tab as shown below Note 1 Ifthe profiler table is empty and the run configuration includes a settings file first make sure the Collect profiling information option is turned on in the Language General window of the settings editor 2 The figures shown in the illustrati
115. ons may be different on your machine Each column header is a sort criterion see Sorting and there are two icons at the top right of the Profiler tab for the commands Copy contents to clipboard and Customize thresholds The Description column presents the execution steps in sequential order as a tree The root item corresponds to the full execution 2 Problems El Scripting log Solutions Conflicts Relaxations 2 2 Engine log 3 Statistics Profiler 52 gi r u Description Time Time PeakMemory Peak Memory Self Time Self Time Local Memory Local Memory Count Nodes 2812 a ioo or ST ne READ DEFINITION profiler 0 0000 0 0 0 0 0000 0 128 0 1 1 LOAD MODEL profiler DEAEA1D8 0 4531 62 1 740 800 31 0 0000 0 944 256 97 1 12 PRE PROCESSING 0 4531 62 1 736 704 31 0 0000 O 942 904 9795 1 11 EJ EXECUTE INIT valuest 0 2500 34 1 085 440 20 0 2344 83 458 120 4795 1 4 S INITr 0 0000 0 0 0 0 0000 0 656 0 1 2 INIT n 0 0000 0 0 0 0 0000 0 104 0 1 1 INIT Values 0 0156 2 454 656 8975 0 0156 6 455 800 4795 1 1 S EXECUTE INIT_Values2 0 1875 26 651 264 12 0 1250 44 456 888 479 1 2 INIT Values2 0 0625 9 0 0 0 0625 22 456 440 4735 1 1 S EXECUTE INIT Values3 0 0156 2 Q 0 0 0000 0 27 768 3 1 4 S INIT Values3 0 0156 2 0 0 0000 0 27 320 3 1 3 i INIT indexes 0 0156 295 0 0 0 0156 6 25 200 395 1 2 INIT T 0 0000 0 0 0 0 0000 0 296 0 1 1 EXTRACT profiler 0EAEA1D8 0 0000 0 0 0 0 00
116. ontrolling MIP node log display information MIPDisplay is set to 1 or higher If MIPDisplay is set to 2 or higher then for any node whose number is a multiple ofthe MIPInterval value a line is recorded in the node log for every node with an integer solution CPLEX logs an asterisk in the left most column for any node where it finds an integer feasible solution or new incumbent In the next column it logs the node number It next logs the number of nodes left to explore In the Objective column CPLEX either records the objective value at the node or a reason to fathom the node A node is fathomed if the solution of a subproblem at the node is infeasible or if the value of the objective function at the node is worse than the cutoff value for branch amp cut or if the linear programming relaxation at the node supplies an integer solution This column is left blank for lines that report that CPLEX found a new incumbent by primal heuristics A plus after the node number distinguishes such lines ILOG OPL IDE TUTORIALS In the column labeled IInf CPLEX records the number of integer infeasible variables and special ordered sets If no solution has been found the column titled Best Integer is blank otherwise it records the objective value of the best integer solution found so far The column labeled Cuts Best Node records the best objective function value achievable If the word Cuts appears in this column it means various cuts were
117. or details if necessary IBM ILOG OPL IDE TUTORIALS 441 42 B M ILOG OPL D E TUTORIALS Working with external data Explains how to connect to data sources from OPL based on the example of databases and then provides two practical cases In this section Purpose and prerequisites Describes the type of model used and outlines the assumed knowledge Using data sources As an example of working with databases explains how to connect to a database using OPL instructions The oil database example Describes the oil database tables and project and its execution The oil sheet example Describes the oil data spreadsheet the oil sheet project and its execution IBM ILOG OPL IDE TUTORIALS 43 Purpose and prerequisites IBM ILOG OPL allows you to read data from a data source a database or calculation spreadsheet In this case the data is said to be external to OPL As opposed to the data in an internal OPL dat file The tutorial uses a model solved by the CPLEX engine but all the features described work in the same way with a model solved by the CP Optimizer engine Both examples are variants of a blending application This tutorial therefore assumes that you know how to define instantiate and initialize data see Data sources in the Language Reference Manual you know how to work with projects in the IDE see Getting Started tutorial you are familiar with the blending applicati
118. order Rt Problems Ed Scripting log e i Solutions Conflicts Relaxations e Engine log amp Statistics Profiler 23 Bro Description Time Time Peak Memory Peak Memory Self Time Self Time Local Memory Local Memory Count Nodes ROOT 0 7344 100 5 533 696 100 0 2812 100 975 032 100 1 18 LOAD MODEL profiler DEAEA1D8 0 4531 62 1 740 800 31 0 0000 0 944 256 97 1 12 PRE_PROCESSING 0 4531 62 1 736 704 31 0 0000 0 942 904 97 1 11 EXECUTE INIT _Values1 0 2500 34 1 085 440 20 0 2344 83 458 120 4795 1 4 EXECUTE INIT_Values2 0 1875 26 651 264 12 0 1250 44 456 888 47 1 2 INIT Valuest 0 0156 296 454 656 895 0 0156 6 455 800 47 I 1 CPLEX Solve LP Relaxation 0 0000 0 86 016 2 0 0000 0 86 016 995 1 2 READ DEFINITION profiler 0 0000 0 0 0 0 0000 0 128 0 1 1 INITr 0 0000 0 0 0 0 0000 0 656 0 1 2 INITn 0 0000 0 0 0 0 0000 0 104 0 1 1 INIT Values2 0 0625 9955 0 0 0625 22 456 440 4795 1 I EXECUTE INIT Values3 0 0156 2 0 0 0 0000 0 27 768 3 1 4 INIT Values3 0 0156 2 0 0 0000 0 27 320 3 1 3 INIT indexes 0 0156 2 0 0 0156 6 25 200 3 1 2 INIT T 0 0000 0 o 0 0 0000 0 296 0 1 1 EXTRACT profiler OEAEA1D8 0 0000 0 a 0 0 0000 0 168 0 1 1 CPLEX Pre Solve 0 0000 0 0 0 0 0000 0 0 0 1 1 POST_PROCESSING 0 0000 0 0 0 0 0000 0 256 0 1 1 lt E writable Insert 28 2 OPL Basic Configuration 100 eD Profiler table sorted on the peak memory column profiler mod Thresholds Click the Custo
119. overing ops ype parameter description fiter Error imi E B5 Mathematical programming 2 a Constraint Programming EY 50 E amp Language Postprocess feasible solutions V E FI General HET z Run Display solution M BR Display relaxations M Ba Display conflicts v E Rn Collect profiling information v zm cone te B Export format No export x B n Turning on the Postprocess feasible solutions option 4 Re run Basic Configuration in the covering project to execute the covering example again and postprocess any feasible solutions found before the final solution Result 112 IBM ILOG OPL IDE TUTORIALS At the end of execution observe the difference in the Scripting log It contains two sets of output written by the engine and by the postprocessing script one for the feasible solution and one for the final solution E Problems Solutions Conflicts Relaxations amp Engine log Statistics 5 Profiler feasible solution with objective 27 Crew 9 10 11 12 14 16 17 18 20 21 M solution optimal with objective 14 IlCrew 23 25 26 Postprocessing a feasible solution covering project The non optimal feasible solution appears because the Postprocess feasible solutions was checked IBM ILOG OPL IDE TUTORIALS 113 114 IBM ILOG OPL IDE TUTORIALS Relaxing infeasible models Uses the nurses example to demonstrate how the IDE detects conflicts and searches for relaxations in
120. ple scalableWarehouse mod int Fixed 10 int NbWarehouses 50 int NbStores 200 assert NbStores NbWarehouses range Warehouses 1 NbWarehouses range Stores 1 NbStores int Capacity w in Warehouses NbStores div NbWarehouses w NbStores div NbWarehouses int SupplyCost s in Stores w in Warehouses db we 4 S o ALG sy 3 e ALON he dvar int Open Warehouses in 0 1 dvar float Supply Stores Warehouses in 0 1 dexpr int TotalFixedCost sum w in Warehouses Fixed Open w dexpr float TotalSupplyCost sum w in Warehouses s in Stores SupplyCost s w Supply s w minimize TotalFixedCost TotalSupplyCost subject to forall s in Stores ctStoreHasOneWarehouse sum w in Warehouses Supply s w 1 forall w in Warehouses ctOpen sum s in Stores Supply s w lt Open w Capacity w 148 BM ILOG OPL IDE TUTORIALS Executing the scalable run configuration Basic Configuration is predefined as the default run configuration Since it is not the configuration you want to work on you will first make another run configuration the default one To execute the run configuration 1 Right click Scalable data and choose Set as default The word default appears in parentheses after the run configuration name 2 Right click on Scalable data and select Run this If necessary see Executing a project in Getting Started with the IDE for a reminder of the execution proce
121. rays 54 CPLEX parameters setting 96 debugging 98 displaying data 97 executing 95 filtering solutions 163 OPL options setting 96 prerequisites for database connection 45 Problem Browser displaying data structure 24 navigating the model file 24 solution pool 159 processing time vs user time 143 profiler example 136 Profiler output tab analyzing contents 146 description of contents 142 IBM ILOG OPL IDE profiling model execution 136 profiler example 140 scalable warehouse example 148 Progress chart 19 35 projects executing nurses example 119 profiler example 141 scalable warehouse example 18 149 quadratic constraints number displayed in Statistics output tab 21 range filters for the solution pool 163 reading columns cells from a spreadsheet 69 columns rows from a database 55 red dot 85 red exclamation mark red star default value changed 26 red status indicator 89 relational database See database connection 48 Relative MIP gap tolerance MIP Tolerances option 26 relaxations setting the relaxation level 133 suggested for infeasible models 116 Relaxations output tab 119 relaxing infeasible models 115 removing breakpoint 85 98 results of database update viewing 60 storing in a spreadsheet 70 viewing in a spreadsheet 73 run configurations executing using the Debug button 85 tuning model performance 172 Run to Cursor button 89 running state 18 scalableWarehouse mod model for the warehouse pro
122. red 89 status messages after execution 24 Step Into button 89 90 99 102 104 Step Out button 101 103 Step Over button 85 88 90 99 101 stepping when debugging a script 88 storing results in a spreadsheet 70 table loading 54 thisOplModel implicit model 88 thresholds in Profiler table 144 time measured in Profiler table 136 time limit 96 tolerances MIP 26 tooltips values in tuple set 99 transportation problem preprocessing scripts 91 presentation 92 tuning process 172 181 temporary files 183 with fixed settings 180 tuple arrays in oil sheet example 67 in oil spreadsheet example 67 tuple sets in call stack 99 in oil database example 54 tuples in oil database example 53 in oil sheet example 67 tutorials connection to a database or spreadsheet 44 IBM ILOG Script for OPL 76 infeasible models 116 profiling a model 136 progress chart 13 30 solution pool 156 tuning a model 172 updating a database 56 viewing the result 60 user time vs processing time 143 variables display via scripting 97 viewing contents of spreadsheets 65 results in spreasheet 73 OPL IDE TUTORIALS 189 results of database update 60 tables in a database 50 warehouse example 136 148 159 172 solution pool 156 warehouse location problem execution of run configuration with scalable data 18 presentation 14 warehouse project tuning tool 176 warm start 88 190 IBM ILOG OPL IDE TUTORIALS
123. respect a format that depends on the target RDBMS For an example of connecting to an Oracle database see Connection to Oracle For an example of connecting to a Microsoft amp Access database through ODBC connectivity see The oil database example Connection to Oracle If you are using an Oracle database you should adapt the DBConnection statement to this case For example in this connection string IBM ILOG OPL IDE TUTORIALS 45 46 B M DBConnection db oracle9 scott tiger ilog the user scott with the password tiger wants to connect to the Oracle database called ilog The string passed as first argument must take the value oraclex where x depends on the version of Oracle that the DB Link driver was built upon A possible value is oracle9 The connection string passed as second argument must respect the format user password SQL Net id where 9 user and password indicate the user name and the password that the database administrator has already assigned to you the field SOL Net id has the format instance name for SQL Net V2 ILOG OPL IDE TUTORIALS The oil database example Describes the oil database tables and project and its execution In this section Description of the example Includes what you will learn and where to find the files The oil database tables Describes how to view the contents of these tables via Microsoft Access The oil database project Describes th
124. rkTime 40 40 40 40 0 4 40 40 40 30 40 30 4 o NurseAvgHours 35 438 EP NurseMoreThanAvgHours 4 5625 4 5625 4 5625 4 5625 0 562 E NurseLessThanAvgHours 00003632000606000000 Fairness 240 amp XY Constraints 6 ET ctRequiredAssignmentConstrain NurseAssignments n s ET ctNurseMaxTimeConstraints F NurseWorkTime n lt 40 ET ctNurseIncompatConstraints NurseAssignments n1 s NurseAssign Ff ctNurseAssocConstraints NurseAssianments n11 s NurseAss Property Value Problem Browser scrolling to variables NurseAssignments 3 Click the Show data view button in the NurseAssignments row The table of nurse assignments opens as shown IBM ILOG OPL IDE TUTORIALS 129 Nurses size 32 Shifts size 35 name startTime endTime n Value 1 1 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 A table view of NurseAssignments The second line shows that Anne is assigned to Emergency Monday 8 12 For further information on views of model elements see Understanding the Problem Browser in Getting Started with the IDE Now you may want to know more on How relaxation and conflict search works 130 IBM ILOG OPL IDE TUTORIALS How relaxation and conflict search works Relaxations and conflicts both express the infeasibility of a model and propose steps towards feasibility After you have had hands on experience with the nurse scheduling example learn how to differentiate between
125. s are displayed in the Solutions tab If you select pool solution 1 this solution will be displayed in the Solutions tab If you select pool solution 2 both 1 and 2 will be displayed By default the pool collects the feasible solutions if any that is all the solutions that worked out at the cost of not satisfying the objective by a certain gap You can use option settings to collect more of these non optimal solutions ILOG OPL IDE TUTORIALS Obtaining more solutions If you realize after a MIP optimization that you need additional solutions you can set the IDE to show more of them by activating the Populate solution pool option The number of solutions you see depends on the values you select for the associated MIP Solution pool options These options set CPLEX to spend some extra time after the search to find more feasible solutions by using some specific strategies To obtain more solutions 1 Add a settings file to the Scalable data configuration as explained in Adding a settings file in Getting Started wit h the IDE In the settings editor select Mixed Integer Programming gt Solution pool Check the Populate solution pool box 8 warehouse ops 3 Type Parameter description filter Mathematical programming General Conflicts Emphasis Feasopt Preprocessing Read Tune amp Simplex B E Mixed Integer Programming General Strategy Limits Tolerances Cuts Solution pool H Barrier H E Network
126. s how the script performs iterations to solve the model Debugging a flow control script Describes breakpoint management call stack display variable object examination and stepping IBM ILOG OPL IDE TUTORIALS 79 Presenting the multiperiod production planning example 80 B M The multiperiod production planning example is a generalization of the single period pasta production example described in A production problem in the Language User s Manual The multiperiod version considers the demand for the products over several periods and allows the company to produce more than the demand in a given period There is an inventory cost associated with storing the additional production The approach to solving this mathematical programming problem is described in detail in A multi period production planning problem in the Language User s Manual This section assumes that you are familiar with the solving strategy as explained in that document The file mulprod_main mod contains the flow control script to implement the solving strategy See the code sample The flow control script mulprod_main mod A flow control script is encapsulated in a main statement main The main statement can be anywhere in the model file but usually follows the OPL statements for the model See Tutorial Flow control and multiple searches in the Language User s Manual What you are going to do Working from the example described in Presenti
127. s tab oilSheet dat You can examine the data and variables in tabular form from the data structure tree built in the Problem Browser You can also see all the results together in Microsoft Excel ILOG OPL IDE TUTORIALS Viewing the result in the spreadsheet When you have successfully executed the model in the IDE you can view the contents of RESULT in the spreadsheet 1 Reopen the spreadsheet file oilSheet x1s from Microsoft Excel 2 Click the RESULT tab to see the contents IBM ILOG OPL IDE TUTORIALS 73 The RESULT sheet after execution The RESULT sheet gives the results in rows for each crude gasoline combination It shows the blend as a number of barrels of each crude used for each type of gasoline and the amount spent on advertising that type of gasoline The RESULT sheet 74 IBM ILOG OPL IDE TUTORIALS Using IBM ILOG Script for OPL Teaches the features of the IDE for scripts written in IBM ILOG Script for OPL including the script debugging facilities In this section Purpose and prerequisites Describes the types of models used and outlines the assumed knowledge Features of IBM ILOG Script for OPL Briefly explains what you can do with IBM ILOG Script for OPL and introduces the main and execute statements The multiperiod production planning example Presents the example and explains how to execute it and debug the flow control script The transportation example Presents the example and explains
128. set in the OPL settings The tuning can be done for one or several run configurations so that the search performs best when your application is deployed Because in a deployed application data changes between each invocation of the engine performance tuning can be executed on a set of problem instances Prerequisites The tutorial assumes that you know how to work with projects in the IDE If this is not the case read Getting Started with the IDE first Where to find the files The tutorial is based on the warehouse project available at the following location lt OPL_dir gt examples opl1 warehouse where OPL dir is your installation directory The warehouse location problem is described in Warehouse location problems in the Samples manual Note You will open this OPL project and all projects in these tutorials using the New Example wizard which allows you to open and work with a copy of the distributed example leaving the original example in place If you need a reminder of how to use the New Example wizard see Opening distributed examples in the OPL IDE ILOG OPL IDE TUTORIALS How performance tuning works The tuning tool works as follows It considers one or more run configurations you specify If the run configurations selected contain different models the tuning process generates a sav file for each selected configuration and optimizes the parameters for all these sav files considered together Ev
129. sing execute blocks before the objective as shown below Preprocessing statements transp4 mod execute PARAMS cplex tilim 100 execute SETTINGS settings displayComponentName true settings displayWidth 40 writeln Routes Routes execute DISPLAY function printRoute r verte Ca a ED MT writeln r e o gt r e d writeln Routes for var r im Routes 4 printRoute r The data is initialized in the transp4 dat data file You can double click transp4 dat to open that file in the editing area if you want to follow along with what is being described below Note that the tuple set TableRoutes is database friendly in that it would allow the loading of data on routes and costs with a single SELECT statement In this example the tuples in set TableRoutes and in arrays Supply and Demand are explicitly initialized in the data file because the matrix is sparse and only some tuples exist The model requires routes and costs separately so in the model file the tuples in tuple set Routes are derived from those in TableRoutes and the tuples in sets Supplies and Customers are then derived from those in Routes ILOG OPL IDE TUTORIALS Executing preprocessing scripts Basic Configuration is the default run configuration in this project but it does not contain the preprocessing scripts you will be working with So in the steps below you run the Even better sparsity run configuration Right c
130. sing the SheetRead statement as in oilSheet dat Reading spreadsheet cells 0i1Sheet dat Gas from SheetRead sheet gas B2 E4 Oil from SheetRead sheet oil B2 E4 Note that the columns read are B to E not A and the cells read are from 2 upward as the name column is not used and the names of the other columns are not stored in the data arrays Note also that the data file initializes some variables directly it does not only take data from the spreadsheet Writing the results to the spreadsheet At the end of the optimization process you need to store the optimal blends and advertising expenditures in the RESULTS sheet You can insert the oil gas blend and a arrays as columns in the RESULT sheet using a SheetWrite statement Writing results to a spreadsheet oilSheet dat a to SheetWrite sheet RESULT A2 A4 Blend to SheetWrite sheet RESULT B2 D4 ILOG OPL IDE TUTORIALS Executing the oil sheet example To execute the oil sheet example 1 First make sure the spreadsheet file is not read only then close it so that the IDE can write to it If the spreadsheet file is read only the IDE displays an error message 2 Exit Microsoft Excel Otherwise the spreadsheet file is considered read only and the IDE reports an error message 3 Right click the run configuration Data from spreadsheet and make it the default run configuration 4 Right click again and select Run this
131. ss The model solves with no error message 3 Click the Profiler tab in the Output window The next step consists in Examining the extraction and search information IBM ILOG OPL IDE TUTORIALS 149 Examining the extraction and search information 150 B M The extraction search and execution information is collected in a table as explained in Description of the profiling information E Problems E Scripting log 4 Solutions Conflicts Relaxations 2 Engine log Wy Statistics 55 Profiler 3 Time threshold _ 10 Memory threshold i 50 Description Time Peak Memory PeakMemory Self Time Self Time Local Memory Local Memory Count Nodes ROOT 7 3125 34 742 272 100 0 6094 100 19 564 744 100 1 87 CPLEX MIP Optimization 6 5313 19 181 568 55 0 1406 23 11 792 384 60 1 65 CPLEX Branch and Bound 4 4531 3 387 392 10 0 7812 128 1 871 872 10 1 12 CPLEX Solve LP Relaxation 2 0000 40 960 0 0 0312 5 139 0 1497 2 CPLEX Solve LP Relaxation 1 9688 40 960 0 1 9688 323 139 0 1493 1 CPLEX Branch and Bound 1 4668 2 240 512 6 0 5000 82 712 704 4 1 12 CPLEX Heuristics 0 5938 2 338 816 Ts 0 1719 28 48 617 0 115 3 CPLEX Generating Cuts for other Nodes 0 5469 626 688 2 0 2188 36 14 0 11003 CPLEX Variable Selection 0 4844 86 016 0 0 3594 59 301 0 1492 2 CPLEX Solve LP Relaxation 0 4219 o 0 0 0312 5 110 0 667 2 CPLEX Solve LP Relaxation 0 4062 o 0 0 0156 3 1 714 0 5
132. ssing time vs user time All figures indicated in the Time column are processing times not user times This means that if your computer is executing other tasks at the same time or is paging because it has too much memory to handle these extra times are not taken into account by the profiler In other words the OPL profiler records the user kernel time which Microsoft amp calls the process time given the following definitions elapsed time The total elapsed wall clock time required for an operation This includes time spent waiting for I O synchronization objects timers scheduling and other delays user kernel time The amount of time executing code in the thread It does not include time spent waiting for devices or servicing other processes Sorting By default the Profiler table rows are sorted sequentially in the order of execution as reflected by the Description tree However you can sort the table in ascending or descending order on the figures of any column by clicking on that column header name IBM ILOG OPL IDE TUTORIALS 143 For example in Profiler table sorted on the peak memory column profiler mod the figures in the Peak Memory column are sorted in descending order and as a consequence the Description tree is no longer displayed sequentially Compare to Profiling information for the profiler example which shows the default sequential order Click the Description column header to restore the default
133. stance int Fixed 30 int NbWarehouses 50 int NbStores 100 when the pool is populated 6 solutions out of the range defined in the filter are removed 26 without the filter 20 with the filter To observe filter scripts 1 Select the warehouse project 2 Right click the run configuration name Filter script and choose Set as Default 3 Add a settings file as explained in Adding a settings file in Getting Started with the IDE to the Filter script configuration 4 In the settings editor scroll down the option tree and click Mixed Integer Programming gt Solution pool 5 Check the Populate solution pool box 6 Execute the run configuration You can also add diversity filters using the method cplex addDiversityFilter See the IBM ILOG Script Reference Manual IBM ILOG OPL IDE TUTORIALS 165 146 IBM ILOG OPL IDE TUTORIALS Flow control script and solution pool Describes how to use the IBM amp ILOG Script API to populate the solution pool and use the solutions found In this section How the flow control script works Illustrated via the model solpoolscript mod Executing the flow control script Using the warehouse project IBM ILOG OPL IDE TUTORIALS 167 How the flow control script works The model solpoolscript mod is a variation of scalableWarehouse mod and has been written to illustrate how the flow control script works It contains the main flow control script shown in the following code extract
134. supply string p string o Supplies lt p bands o GARY gt n lt p 9 Supply 400 700 800 800 1600 1800 200 300 customer tuple customer string p string d 4 Customers lt p bands d FRA gt lt p bands Demand 300 300 100 75 650 225 250 500 750 settings a IloOplSettings amp 4 with object Object this object Object or lt p bands e lt o CLEV d STL gt IloOplInputFile primitive constructor IloOplInputFile Nj The Variables view after stepping Stepping out of an execute function If you are stepping in an execute statement and the current instruction is within a loop or forall while Or repeat you can make the IDE execute the loop without stopping at instructions by stepping out of the execute function using the Step Return button The IDE executes the entire loop then stops at the first instruction after the loop The Step Return button allows you to step out of a function in a script to the statement following the function call For example if you were to click the Step Return button at this statement writeln Routes the current instruction becomes IBM ILOG OPL IDE TUTORIALS 101 102 B M for var r in Routes E 9execute SETTINGS settings displayComponentName true settings displayWidth 40 writeln Routes Routes nono Cn Cn WN KH Cc ON o rs 65execute DI
135. t you are going to do Working from the nurse scheduling example you will become familiar with the nurses project see Setting up the nurses model and data solve the model and discover that it is infeasible see Executing the nurses project 1 analyze and understand the suggested relaxation see Studying the suggested relaxation ILOG OPL IDE TUTORIALS analyze and understand suggested conflicts see Studying the suggested conflicts change some data see Changing the data execute the project again and find a solution to the feasible model Executing the nurses project 2 learn more about How relaxation and conflict search works Important Conflicts and relaxations are supported only for models solved by the CPLEX engine They are not currently supported with the CP Optimizer engine Where to find the files The project folder is at the following location lt OPL_dir gt examples opl nurses where OPL dir is your installation directory Note You will open this OPL project and all projects in these tutorials using the New Example wizard which allows you to open and work with a copy of the distributed example leaving the original example in place If you need a reminder of how to use the New Example wizard see Opening distributed examples in the OPL IDE IBM ILOG OPL IDE TUTORIALS 117 Setting up the nurses model and data Use the File gt New gt Example menu command to open the nurses example The ID
136. ted IBM ILOG OPL IDE TUTORIALS 89 90 B M 2 3 mulprod Solve models sequence by changing data OPL Run Configuration terminated OPL mulprod Solve models sequence by changing data termi i Aborting the execution of a script in debugging mode 2 After aborting you can relaunch the script by clicking the Debug button Ending execution To summarize while stepping through a script you can end execution in one of three ways 1 Click the Continue the current solve button the IDE completes the script 2 Click the Abort the current solve button the script terminates without being completed 3 Clickthe Step Over button or Step Into button if there are no functions repeatedly the IDE completes the script instruction by instruction Examining the output The output of execution is displayed in the Scripting log 393 6666666666667 capFlour 70 393 9 capFlour 71 393 5 10 00 100 0 0 50 0 0 gt 20 0 0 50 150 0 4x75 25 0 gt 50 0 0 0 100 0 lt 0 100 051 ILOG OPL IDE TUTORIALS The transportation example Presents the example and explains how to execute it and debug the preprocessing script In this section Presenting the transportation example Summarizes the problem and explains what to do and where to find the files Setting up the transportation model and data Describes the model and data files Executing preprocessing scripts
137. tes for var r in Routes printRoute r 75 76 string Orig p in Products c o lt p c gt in Routes 77 string Dest p in Products c d lt p c gt in Routes 78 79 connection CPs p in Products c lt p c gt in Routes 80 v K a E Execution stopped at the breakpoint in transp4 mod Examining the preprocessing call stack The call stack showing nested function calls is displayed in the Debug view The content of a selected call frame is displayed in the Variables view In this example the call stack contains one call frame transp4 mod 66 m L3 AM ESR E gj terminated transp Even better sparsity OPL Run Configuration cf terminated OPL transp Even better sparsity transp Even better sparsity OPL Run Configuration OPL Projects S a OPL transp Even better sparsity S preProcessing transp4 mod suspended at breakpoint transp4 mod 66 Debug view for transp4 mod IBM ILOG OPL IDE TUTORIALS 99 100 B M er with amp Cities amp 4 Products 9 Capacity tableRoutesType TableRoutes connection route Routes supply Supplies Supply customer Customers IloOplInputFile a IloOpIModel GARY CLEV PITT FRA DET L bands coils plate 625 tuple tableRoutesType string p strin E p bands o GARY d FRA cost tuple connection string o string d tuple route string p tuple e
138. the line written by the postprocessing script Problems E Scripting log 3 C Solutions 74 Conficts Relaxations 5 Engine log statistics 5 Profiler y solution optimal with objective 14 Crew 23 25 26 Scripting log output written by the engine and a script covering project The line written to the Scripting Log by the postprocessing script shows the crew that is the workers that are hired Three out of thirty two workers are used in this solution IBM ILOG OPL IDE TUTORIALS 111 Postprocessing a feasible solution You are now going to change an OPL Language option for the covering project and observe the different output in the Scripting Log after execution First you need to add a settings file to that project if it does not already exist To change an OPL Language option for a project 1 Right click the covering project in OPL Projects Navigator and choose New gt Settings to create a settings file as explained in Adding a settings file in Getting Started with the IDE 2 Name it covering ops and add it to the default run configuration using drag and drop After you have done this the various MP CP and OPL Language options become visible in the settings editor 3 Click Language gt Run then check the Postprocess feasible solutions box and save the settings file Note the red exclamation mark indicating that the option is set to a user defined value T c
139. ther or not the worker is hired The file covering mod contains the postprocessing script which manipulates the results data to show the resulting crew of hired workers See Postprocessing script covering mod A postprocessing script is encapsulated in an execute statement execute 1 The execute statement for postprocessing must follow the objective function in the model file What you are going to do Working from the covering example described above you will set up the model and data see Setting up the covering model and data run the default configuration including the postprocessing script as explained in Executing a postprocessing script and then examine the Scripting Log tab change an OPL Language option rerun the model and see the difference in the Scripting Log tab Where to find the files The covering example is supplied in the covering project at the following location lt OPL_dir gt examples opl covering where lt OPL_dir gt is your installation directory The model for the covering project is contained in the file covering mod Data for the model covering mod is contained in the file covering dat ILOG OPL IDE TUTORIALS Note You will open this OPL project and all projects in these tutorials using the New Example wizard which allows you to open and work with a copy of the distributed example leaving the original example in place If you need a reminder of how to use the New Exampl
140. tings in performance tuning process 180 flow control 80 and the solution pool 167 debugging a script 85 executing a script 83 function IBM ILOG Script keyword used in an execute statement 97 functions in an execute block 97 generic indexed arrays in oil database example 54 getConflict method IloCplex class 134 green status indicator 24 89 IBM ILOG Script executing 83 111 112 multiperiod production example 79 stepping out into a loop 102 tutorial 76 IBM 6 ILOG Script Objects window 86 87 idle state 24 90 IloCplex class getConflict method 134 IloOplIModel class 88 infeasible models 115 116 initializing arrays via scripting 96 integer division operator 16 integer programming 106 integer solutions notification 24 intermediate solutions postprocessing 112 iterations in flow control script 84 JavaScript definition 76 kernel time 143 keywords DBConnection 45 55 IBM ILOG DBExecute 56 DBRead 55 SheetConnection 69 SheetRead 69 SheetWrite 70 labeling constraints 132 linear programming 48 lines end of 82 loops monitoring 92 103 main IBM ILOG Script block in multiperiod production planning example 80 last expression value in the Scripting Log tab 84 memory consumption by model elements 139 146 displayed in Profiler table 136 MIP example 13 30 156 solution pool 156 tolerances 26 models blending 44 covering 105 106 extraction and solving info in Profiler table 147 infeasible 116
141. tion about execution time memory consumption and model extraction collected after execution of the model Examining the profiling information Explains how to analyze time and memory consumption after execution of the model IBM ILOG OPL IDE TUTORIALS 139 Presenting the profiler example 140 B M The profiler example is a variation of the transportation example see Profiling in the Samples manual Use the File gt New gt Example menu command to open the profiler example The IDE displays the profiler project in the OPL Projects Navigator Open the model in the editing area Model of the Profiler example profiler mod antem 93005 range r T n int Valuesl r r execute INIT Valuesl FOXU Wee Gly ge ae roned Weld g sg 3e if i 2 j Valuesl i j i j writeln Values1 ink Values 2 ia oba ae 4 Aneel S2 2 dej sr execute INIT Values2 writeln Values2 tuple T aint das aloe 9 8 GE since d ah Bosal 2 E Gba Ge he int Values3 1 in indexes 143 execute INIT Values3 writeln Values3 The profiler example is supplied with no data file This example is a dummy unrealistic model where the same data is created in three different ways so as to demonstrate how the profiler helps you find which data is slow and or memory consuming The code extract above shows that the identical data to be created is a structure of values depending on two indices i and j N
142. tion with scalable data and examine the resulting statistics and chart IBM ILOG OPL IDE TUTORIALS 17 Executing the warehouse project with scalable data 18 B M Basic Configuration is predefined as the default run configuration to be executed Since itis not the configuration you want to work on you will first make another run configuration the default one The scalable model has been designed to be solved by the CPLEX engine in several seconds so that you have time to observe and interact with the execution process To experience such interaction and observe the results you are now going to start then suspend the execution and observe the output in the Statistics tab 1 Right click on Scalable data and choose Set as Default This configuration name is now labeled as the new default 2 To execute this run configuration right click on Scalable data and select Run this 3 In the Execution toolbar the Pause the current solve button di appears Click this button just after launching the solve to interrupt the process and examine the current solution See What happens when you execute a run configuration in the IDE Reference for details 4 Click the Statistics tab See Examining the statistics and progress chart MP to understand what you see at this stage of the execution process 5 The Pause button is replaced with the Continue the current solve button Click to continue and wait until execution is complete
143. tuning tool Describes how to improve the combination of parameters for the CPLEX part of your model s IBM ILOG OPL IDE TUTORIALS About IDE tutorials This manual assumes that you are familiar with the IDE graphical user interface Read Getting Started with the IDE first if this is not the case You may also need to read How to read the OPL documentation for details of prerequisites conventions documentation formats and other general information This manual is organized as follows Understanding solving statistics and progress MP models A relatively long MIP example presents the pause feature and the display in the Progress chart of the Output window Understanding solving statistics and progress CP models An example that uses a manufacturing problem solved by the CP Optimizer engine to describe the Statistics and Progress chart in the IDE Output window Working with external data An IP example presents the use of a database through SQL instructions in the data file the example database is a Microsoft amp Access file accessed through ODBC connectivity Using IBM ILOG Script for OPL Several examples illustrate the use of scripting through script statements in model files the scripting language is IBM ILOG Script for OPL Relaxing infeasible models The nurse scheduling example illustrates how to use the IDE to search for relaxations and conflicts in an MP model that appears infeasible after execution This feat
144. turns some constraint that may be in the conflict This corresponds to the ConflictPossibleMember status of the method IloCplex getConflict 1344 BM ILOG OPL IDE TUTORIALS Profiling the execution of a model Explains how the IDE Profiler table can help you improve your model to make it run faster while consuming less memory In this section Purpose and prerequisites Explains what to do in this tutorial and where to find the files Identifying slow and memory consuming model elements The information displayed in the table of the Profiler enables you to identify slow or memory consuming elements during execution of the profiler model and possibly to infer what changes in your model might improve execution performance This part of the tutorial uses the profiler example to demonstrate this Examining model extraction and solving In addition to time and memory consumption the Profiler table displays the extraction and solving phases of the model execution This part of the tutorial uses the scalable configuration of the warehouse example to demonstrate this IBM ILOG OPL IDE TUTORIALS 135 Purpose and prerequisites 136 B M When you execute a run configuration information about execution time memory consumption and model extraction is collected as part of the execution When execution stops the information appears as a table in the Profiler output window This tutorial uses models solved with the CPLEX engine
145. ues1 0 25 3496 1 085 440 20 83 458 120 AT 96 EXECUTE INIT Values2 0 1875 26 551 264 1296 44 456888 4796 INIT Values2 0 0625 996 0 0 22 456 440 4796 INIT Values 0 0156 2 454 656 896 6 455 800 4796 EXECUTE INIT Values3 0 0156 2 0 0 0 27 768 396 INIT Values3 0 0156 2 0 0 0 27 320 396 INIT indexes 0 0156 2 0 0 6 25200 3 READ DEFINITION profiler 0 0 0 0 128 0 INIT r 0 0 0 0 656 0 INIT n 0 0 0 104 0 INIT T 0 0 0 296 0 EXTRACT profiler OEAEA1 D8 0 0 0 168 0 CPLEX Solve LP Relaxation 0 2 0 85015 9 CPLEX Pre Solve 0 0 0 0 0 POST_PROCESSING 0 0 0 256 0 Si M 4 gt nNSheeti Sheet2 Sheet3 The next step consists in Examining the profiling information IBM ILOG OPL IDE TUTORIALS 145 Examining the profiling information 146 B M You are now going to analyze the time and memory figures of the profiler mod example l Note The figures shown in the illustrations may be different on your machine Slow elements In the profiling context slow elements are elements with a bad execution time All three data structures are equivalent see Presenting the profiler example However if you look at the first column Time of the Profiler table you can see that execution of EXECUTE INIT Values1 which includes initializing the structure plus setting the values in the script takes nearly twice as long as execution of EXECUTE INIT Values2 which includes initial
146. uest imposed by the two database systems In the case of ODBC you use a query ILOG OPL IDE TUTORIALS sign as a placeholder while in Oracle you use a column sign followed by a column number with the columns numbered starting from one IBM ILOG OPL IDE TUTORIALS 57 Executing the oil database example To execute the oil database example 1 Right click the run configuration Data from database and make it the default run configuration 2 Right click again and select Run this In the Problem Browser you can examine the model in the usual manner to see the contents of the various data structures in this example If you are not familiar with the Problem Browser see Understanding the Problem Browser in Getting Started with the IDE 9 Variables Breakpoints w amp 78 Super 3000 70 10 1 Regula 2000 6082 Diesel 1000 50 6 1 gt Super 3000 70 10 1 lt Regular 2000 608 2 gt O Diesel 1000 50 6 1 Super Regular Diesel 14000 Crudei 5000 45 12 0 5 Crude2 5000 35 62 Crude3 5000 25 8 3 gt i OiData lt Crude1 5000 45 12 0 5 Crude2 5000 356 2 Crude3 5000 25 8 3 gt f Oils Crude1 Crude2 Crude3 ProdCost 4 amp Decision variables 2 Ea 0 750 0 E Blend 2088 9 2111 1 800 777 78 4222 2 0 133 33 3166 7 200 amp XY Constraints 5 i foral o in Oils sum g in Gasolines Blend o g lt Oil o capacity foral g
147. upplied are already included in the supplied database when you execute the model the table Result is deleted and re created Note If you wanted you could experiment by changing values in these tables before executing the model For example changing the prices in the GasData table to 65 Super and 55 Diesel is shown in the modified GasData table below 2101 x name demand prce octane lead Super 3000 65 10 1 Regular 2000 60 8 2 Diesel 1000 55 6 1 Record a 3 gt gt r of 3 The modified GasData table You do not need to do this before continuing the tutorial This is informational in case you want to modify the data in the tables on your own ILOG OPL IDE TUTORIALS The oil database project In the IDE use the File gt New gt Example menu command to open the oil example The IDE displays the oil project in the OPL Projects navigator Open the model file 0i1DB mod in the editing area Set definitions in the model At the beginning of the model file there are definitions of sets of string values to hold the names of the gasolines and oils Set definitions 0i11DB mod string Gasolines tstringh Calis 24 Tuple definitions in the model These are followed by definitions of tuples for the data as shown in Tuple definitions oilDB mod Tuple definitions o11DB mod tuple gasType string name float demand float price float octane float l
148. ure may help you detect errors in the model or data of your project Profiling the execution of a model A tutorial shows how the IDE can help you improve your model to make it run faster while consuming less memory Working with the solution pool This section explains what solution pools are and how solution pools are populated An example shows how you can use IBM ILOG Script to work with solution pools Using the performance tuning tool This section explains with an example how to use this IDE feature to fine tune CPLEX parameters for MP models IBM ILOG OPL IDE TUTORIALS 9 10 B M ILOG OPL D E TUTORIALS Understanding solving statistics and progress MP models Shows how the IDE displays a dynamically updated progress chart for a mixed integer programming MIP example that takes some time to solve In this section Purpose of the tutorial Describes the type of model used The scalable warehouse example Summarizes the problem The scalable warehouse project Examines the project in the OPL IDE Executing the warehouse project with scalable data Explains how to pause and observe the results of the suspended execution Examining the statistics and progress chart MP Describes the engine log progress chart and statistics table for MP models Examining the engine log Describes the Engine Log tab Examining the results and the data Describes how results are displayed in the IDE after model executio
149. ys needed for the model concerned you can even set the parameter within the model by writing an execute IBM ILOG Script block For an example see Changing CPLEX parameters in the Language User s Manual In the scalableWarehouse example if you increase the relative MIP gap tolerance to 0 05 5 the first solution found is immediately considered to be the final solution because it is at most 3 3333 from the optimal solution as displayed in the notification message To set a CPLEX parameter in the IDE 1 Right click on Scalable data and select New gt Settings to create a settings file with an ops extension Name the file warehouse ops This is explained in Adding a settings file in Getting Started with the IDE 2 Add the new warehouse ops settings file to the run configuration Scalable data using drag and drop 3 Click Mixed Integer Programming gt Tolerances in the option tree on the left 4 Enter the value 0 05 for Relative MIP gap tolerance and press Enter Because this value is not the default value a red exclamation mark appears to the left of the option name 26 IBM ILOG OPL IDE TUTORIALS ype parameter description fitter Absolute MIP gap tolerance Mathematical programming tolera General ony es Conflicts Lower cutoff Emphasis Feasopt Relative MIP gap tolerance Preprocessing Absolute objective difference cutoff Read Tune Relative objective difference cutoff amp Simplex
150. zer search phases and OPL options Add postprocessing instructions to aggregate transform and format data including results data for display or for sending to another application for example a spreadsheet Solve repeated instances of the same model Create algorithmic solutions where the output of one model instance is used as the input of a second model instance Script statements When you use IBM ILOG Script for OPL you avoid having to compile and link you just add script statements to your model file There are two possible top level statements The main statement for a flow control script The execute statement for preprocessing and postprocessing scripts You can also write script statements in data files by using the prepare and invoke keywords Note There are no separate script files you write script statements directly in model files within execute or main blocks 78 IBM ILOG OPL IDE TUTORIALS The multiperiod production planning example Presents the example and explains how to execute it and debug the flow control script In this section Presenting the multiperiod production planning example Summarizes the problem and explains what to do and where to find the files Setting up the multiperiod production model and data Presents the model and data file Executing a flow control script Explains how to change the default run configuration Purpose of the flow control script Explain

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