feasopt_cs.cs
/* Copyright 2021, Gurobi Optimization, LLC */ /* This example reads a MIP model from a file, adds artificial variables to each constraint, and then minimizes the sum of the artificial variables. A solution with objective zero corresponds to a feasible solution to the input model. We can also use FeasRelax feature to do it. In this example, we use minrelax=1, i.e. optimizing the returned model finds a solution that minimizes the original objective, but only from among those solutions that minimize the sum of the artificial variables. */ using Gurobi; using System; class feasopt_cs { 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].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].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].ConstrName); } } // Optimize modified model feasmodel.Optimize(); feasmodel.Write("feasopt.lp"); // 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); } } }
