bilinear_cs.cs
/*版权所有，Gurobi Optim狗万app足彩ization, LLC */ /*本例制定并求解了以下简单双线性模型:最大化x服从x + y + z <= 10 x * y <= 2(双线性不等式)x * z + y * z == 1(双线性不等式)x, y, z非负(第二版中的x积分)*/使用System;使用Gurobi;class bilineear_cs {static void Main() {try {GRBEnv env = new GRBEnv("bilinear.log");GRBModel model = new GRBModel(env);//创建变量GRBVar x = model.AddVar(0.0, GRB。无限，0.0,grb。连续的," x ");GRBVar = model.AddVar(0.0，无限，0.0,grb。连续的," y ");GRBVar z = model.AddVar(0.0, GRBVar;无限，0.0,grb。连续的,“z”);//设置目标GRBLinExpr obj = x;模型。SetObjective (obj GRB.MAXIMIZE); // Add linear constraint: x + y + z <= 10 model.AddConstr(x + y + z <= 10, "c0"); // Add bilinear inequality: x * y <= 2 model.AddQConstr(x*y <= 2, "bilinear0"); // Add bilinear equality: x * z + y * z == 1 model.AddQConstr(x*z + y*z == 1, "bilinear1"); // Optimize model try { model.Optimize(); } catch (GRBException e) { Console.WriteLine("Failed (as expected) " + e.ErrorCode + ". " + e.Message); } model.Set(GRB.IntParam.NonConvex, 2); model.Optimize(); Console.WriteLine(x.VarName + " " + x.X); Console.WriteLine(y.VarName + " " + y.X); Console.WriteLine(z.VarName + " " + z.X); Console.WriteLine("Obj: " + model.ObjVal + " " + obj.Value); x.Set(GRB.CharAttr.VType, GRB.INTEGER); model.Optimize(); Console.WriteLine(x.VarName + " " + x.X); Console.WriteLine(y.VarName + " " + y.X); Console.WriteLine(z.VarName + " " + z.X); Console.WriteLine("Obj: " + model.ObjVal + " " + obj.Value); // Dispose of model and env model.Dispose(); env.Dispose(); } catch (GRBException e) { Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message); } } }
