poolsearch_cs.cs
/* Copyright 2021, 狗万app足彩Gurobi Optimization, LLC */ /*我们找到一个给定的背包问题的替代epsilon-optimal解决方案使用PoolSearchMode */使用系统;使用Gurobi;类poolsearch_cs {static void Main() {try{//示例数据int groundSetSize = 10;double[] objCoef = new double[] {32, 32, 15, 15, 6, 6, 1, 1, 1};double[] knapsackCoef = new double[] {16,8,8,4,4,2,2,1,1};double Budget = 33;int e, status, nSolutions;//创建环境GRBEnv env = new GRBEnv("poolsearch_cs.log");//创建初始化的GRBModel模型= new GRBModel(env);模型。ModelName = "poolsearch_cs"; // Initialize decision variables for ground set: // x[e] == 1 if element e is chosen GRBVar[] Elem = model.AddVars(groundSetSize, GRB.BINARY); model.Set(GRB.DoubleAttr.Obj, Elem, objCoef, 0, groundSetSize); for (e = 0; e < groundSetSize; e++) { Elem[e].VarName = string.Format("El{0}", e); } // Constraint: limit total number of elements to be picked to be at most // Budget GRBLinExpr lhs = new GRBLinExpr(); for (e = 0; e < groundSetSize; e++) { lhs.AddTerm(knapsackCoef[e], Elem[e]); } model.AddConstr(lhs, GRB.LESS_EQUAL, Budget, "Budget"); // set global sense for ALL objectives model.ModelSense = GRB.MAXIMIZE; // Limit how many solutions to collect model.Parameters.PoolSolutions = 1024; // Limit the search space by setting a gap for the worst possible solution that will be accepted model.Parameters.PoolGap = 0.10; // do a systematic search for the k-best solutions model.Parameters.PoolSearchMode = 2; // save problem model.Write("poolsearch_cs.lp"); // Optimize model.Optimize(); // Status checking status = model.Status; if (status == GRB.Status.INF_OR_UNBD || status == GRB.Status.INFEASIBLE || status == GRB.Status.UNBOUNDED ) { Console.WriteLine("The model cannot be solved " + "because it is infeasible or unbounded"); return; } if (status != GRB.Status.OPTIMAL) { Console.WriteLine("Optimization was stopped with status {0}", status); return; } // Print best selected set Console.WriteLine("Selected elements in best solution:"); Console.Write("\t"); for (e = 0; e < groundSetSize; e++) { if (Elem[e].X < .9) continue; Console.Write("El{0} ", e); } Console.WriteLine(); // Print number of solutions stored nSolutions = model.SolCount; Console.WriteLine("Number of solutions found: {0}", nSolutions); // Print objective values of solutions for (e = 0; e < nSolutions; e++) { model.Parameters.SolutionNumber = e; Console.Write("{0} ", model.PoolObjVal); if (e%15 == 14) Console.WriteLine(); } Console.WriteLine(); // Print fourth best set if available if (nSolutions >= 4) { model.Parameters.SolutionNumber = 3; Console.WriteLine("Selected elements in fourth best solution:"); Console.Write("\t"); for (e = 0; e < groundSetSize; e++) { if (Elem[e].Xn < .9) continue; Console.Write("El{0} ", e); } Console.WriteLine(); } model.Dispose(); env.Dispose(); } catch (GRBException e) { Console.WriteLine("Error code: {0}. {1}", e.ErrorCode, e.Message); } } }
