The solution search is done with a call to the member function IloSolver::solve.

    IloEnv env;
    IloNumVar makespan;
    IloModel model = DefineModel(env, 
                                 DueDates,
                                 makespan,
                                 NumberOfActivities);
  
    IloSolver solver(model);
    IloGoal goal = IloRankForward(env, makespan);
    IlcScheduler scheduler(solver);
 
    /* FIRST TRY: TARGETED DUE DATES */
    solver.out() << endl << "----------------------------------------" << endl;
    solver.out() << "First try: targeted due dates" << endl;
 
    if (solver.solve(goal)) {
      solver.out() << "current value of makespan: " 
                   << solver.getMin(makespan) << endl;
      PrintSolution(solver);
    }
    else 
      solver.out() << "No solution! " << endl;
 

However, no solution to the problem is found because some targeted due dates are too strong to be satisfied. We can relax the problem by removing selected constraints and this should lead to a solvable problem. For instance, we could apply the following procedure:

This way of proceeding is too simple and appears to be inefficient because we have no guarantee that we remove the strongest due date constraints.