Decision Optimization

Hello Community,

I'm encountering an issue in my OPL main script where I need to set certain variables to zero before solving the problem. Specifically, I'm trying to set the upper bound (UB) for job 2 to zero. However, even after solving the problem, I still observe a solution for job 2. Could someone assist me with this? Your help would be greatly appreciated.

Thank you.

Here is my constraint where I need the UB to zero:

  forall(j in Jobs)
    LambdaCons:
      sum(s in Good_Schedule: s.Job==j) lambda[s] == Z[j];

var masterDef = thisOplModel.modelDefinition;
var masterCplex = cplex;
var masterData = thisOplModel.dataElements;
var masterOpl = new IloOplModel(masterDef, masterCplex);
masterOpl.addDataSource(masterData);     
masterOpl.generate();

writeln("Upper bound before set ", masterOpl.LambdaCons[2].UB);
masterOpl.LambdaCons[2].UB = 0;

if (masterCplex.solve()) {

        curr = masterCplex.getObjValue();

}

Hi,

to understand what went wrong you can export .lp

In my example https://github.com/AlexFleischerParis/zooopl/blob/master/zooincremental.mod

I added the export

 cplex.exportModel("test.lp");

int nbKids=300;
    float costBus40=500;
    float costBus30=400;
     
    dvar int+ nbBus40;
    dvar int+ nbBus30;
    dvar int+ emptyVar;
     
    minimize
     costBus40*nbBus40  +nbBus30*costBus30;
     
    subject to
    {
     ctKids:40*nbBus40+nbBus30*30>=nbKids;
     
     ctEmpty:0<=0;

    }

    execute DISPLAY_After_SOLVE
    {
    writeln("The minimum cost is ",costBus40*nbBus40  +nbBus30*costBus30);
    writeln("We will use ",nbBus40," 40 seats buses and ",nbBus30," 30 seats buses ");
    writeln();
    }

    main
    {
    thisOplModel.generate();

    writeln("Basic model");

    cplex.solve();
    thisOplModel.postProcess();

    writeln("Let us add a row : saying that nbBus40 and nbBus30 should be equal");

    thisOplModel.ctEmpty.setCoef(thisOplModel.nbBus40,1);
    thisOplModel.ctEmpty.setCoef(thisOplModel.nbBus30,-1);
    thisOplModel.ctEmpty.setBounds(0,0);
    cplex.solve();
    thisOplModel.postProcess();

    writeln("Let us add a column : saying that nbBus50 could also be used and their cost is 700");
    cplex.setObjCoef(thisOplModel.emptyVar,700);
    thisOplModel.ctKids.setCoef(thisOplModel.emptyVar,50);
    cplex.exportModel("test.lp");
    cplex.solve();
    writeln("The minimum cost is ",
    thisOplModel.costBus40*thisOplModel.nbBus40.solutionValue  +thisOplModel.nbBus30.solutionValue*thisOplModel.costBus30
    +700*thisOplModel.emptyVar.solutionValue);
    writeln("We will use ",thisOplModel.nbBus40.solutionValue," 40 seats buses ",thisOplModel.nbBus30.solutionValue,
    " 30 seats buses and "+thisOplModel.emptyVar.solutionValue," 50 seats buses");
    }

and then in test.lp I get

Minimize
 obj1: 500 nbBus40#0 + 400 nbBus30#1 + 700 _emptyVar#2
Subject To
 ctKids:  40 nbBus40#0 + 30 nbBus30#1 + 50 _emptyVar#2 >= 300
 ctEmpty: nbBus40#0 - nbBus30#1  = 0
Bounds
      nbBus40#0 >= 0
      nbBus30#1 >= 0
      _emptyVar#2 >= 0
Generals
 nbBus40#0  nbBus30#1  _emptyVar#2 
End

var masterDef = thisOplModel.modelDefinition;var masterCplex = cplex;var masterData = thisOplModel.dataElements;var masterOpl = new IloOplModel(masterDef, masterCplex);masterOpl.addDataSource(masterData);     masterOpl.generate();writeln("Upper bound before set ", masterOpl.LambdaCons[2].UB);masterOpl.LambdaCons[2].UB = 0;if (masterCplex.solve()) {        curr = masterCplex.getObjValue();}