static void Main(string[] args) { if (args.Length < 1) { Console.Out.WriteLine("Usage: feasopt_cs filename"); return; } try { GRBEnv env = new GRBEnv(); GRBModel feasmodel = new GRBModel(env, args[0]); // Create a copy to use FeasRelax feature later */ GRBModel feasmodel1 = new GRBModel(feasmodel); // Clear objective feasmodel.SetObjective(new GRBLinExpr()); // Add slack variables GRBConstr[] c = feasmodel.GetConstrs(); for (int i = 0; i < c.Length; ++i) { char sense = c[i].Get(GRB.CharAttr.Sense); if (sense != '>') { GRBConstr[] constrs = new GRBConstr[] { c[i] }; double[] coeffs = new double[] { -1 }; feasmodel.AddVar(0.0, GRB.INFINITY, 1.0, GRB.CONTINUOUS, constrs, coeffs, "ArtN_" + c[i].Get(GRB.StringAttr.ConstrName)); } if (sense != '<') { GRBConstr[] constrs = new GRBConstr[] { c[i] }; double[] coeffs = new double[] { 1 }; feasmodel.AddVar(0.0, GRB.INFINITY, 1.0, GRB.CONTINUOUS, constrs, coeffs, "ArtP_" + c[i].Get(GRB.StringAttr.ConstrName)); } } feasmodel.Update(); // Optimize modified model feasmodel.Write("feasopt.lp"); feasmodel.Optimize(); // Use FeasRelax feature */ feasmodel1.FeasRelax(GRB.FEASRELAX_LINEAR, true, false, true); feasmodel1.Write("feasopt1.lp"); feasmodel1.Optimize(); // Dispose of model and env feasmodel1.Dispose(); feasmodel.Dispose(); env.Dispose(); } catch (GRBException e) { Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message); } }
static void Main() { try { // Sample data // Sets of days and workers string[] Shifts = new string[] { "Mon1", "Tue2", "Wed3", "Thu4", "Fri5", "Sat6", "Sun7", "Mon8", "Tue9", "Wed10", "Thu11", "Fri12", "Sat13", "Sun14" }; string[] Workers = new string[] { "Amy", "Bob", "Cathy", "Dan", "Ed", "Fred", "Gu" }; int nShifts = Shifts.Length; int nWorkers = Workers.Length; // Number of workers required for each shift double[] shiftRequirements = new double[] { 3, 2, 4, 4, 5, 6, 5, 2, 2, 3, 4, 6, 7, 5 }; // Amount each worker is paid to work one shift double[] pay = new double[] { 10, 12, 10, 8, 8, 9, 11 }; // Worker availability: 0 if the worker is unavailable for a shift double[,] availability = new double[, ] { { 0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1 }, { 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0 }, { 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1 }, { 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1 }, { 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1 }, { 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1 }, { 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 } }; // Model GRBEnv env = new GRBEnv(); GRBModel model = new GRBModel(env); model.ModelName = "assignment"; // Assignment variables: x[w][s] == 1 if worker w is assigned // to shift s. Since an assignment model always produces integer // solutions, we use continuous variables and solve as an LP. GRBVar[,] x = new GRBVar[nWorkers, nShifts]; for (int w = 0; w < nWorkers; ++w) { for (int s = 0; s < nShifts; ++s) { x[w, s] = model.AddVar(0, availability[w, s], pay[w], GRB.CONTINUOUS, Workers[w] + "." + Shifts[s]); } } // The objective is to minimize the total pay costs model.ModelSense = GRB.MINIMIZE; // Constraint: assign exactly shiftRequirements[s] workers // to each shift s for (int s = 0; s < nShifts; ++s) { GRBLinExpr lhs = 0.0; for (int w = 0; w < nWorkers; ++w) { lhs.AddTerm(1.0, x[w, s]); } model.AddConstr(lhs == shiftRequirements[s], Shifts[s]); } // Optimize model.Optimize(); int status = model.Status; if (status == GRB.Status.UNBOUNDED) { Console.WriteLine("The model cannot be solved " + "because it is unbounded"); return; } if (status == GRB.Status.OPTIMAL) { Console.WriteLine("The optimal objective is " + model.ObjVal); return; } if ((status != GRB.Status.INF_OR_UNBD) && (status != GRB.Status.INFEASIBLE)) { Console.WriteLine("Optimization was stopped with status " + status); return; } // Relax the constraints to make the model feasible Console.WriteLine("The model is infeasible; relaxing the constraints"); int orignumvars = model.NumVars; model.FeasRelax(0, false, false, true); model.Optimize(); status = model.Status; if ((status == GRB.Status.INF_OR_UNBD) || (status == GRB.Status.INFEASIBLE) || (status == GRB.Status.UNBOUNDED)) { Console.WriteLine("The relaxed model cannot be solved " + "because it is infeasible or unbounded"); return; } if (status != GRB.Status.OPTIMAL) { Console.WriteLine("Optimization was stopped with status " + status); return; } Console.WriteLine("\nSlack values:"); GRBVar[] vars = model.GetVars(); for (int i = orignumvars; i < model.NumVars; ++i) { GRBVar sv = vars[i]; if (sv.X > 1e-6) { Console.WriteLine(sv.VarName + " = " + sv.X); } } // Dispose of model and environment model.Dispose(); env.Dispose(); } catch (GRBException e) { Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message); } }