facility_c + + . cpp
/ * 2023年版权,Gurobi优狗万app足彩化,LLC * / / *设施地点:公司目前船舶产品从5植物4仓库。狗万滚球球它正在考虑关闭一些工厂为了降低成本。什么植物(s)公司应关闭,为了减少运输和固定成本?狗万滚球球从前线系统基于一个例子:http://www.solver.com/disfacility.htm使用许可。手机万博登录* / # include“gurobi_c + +。h”# include < sstream >使用名称空间性病;int主要(int命令行参数个数,char * argv []) {GRBEnv * env = 0;GRBVar *开放= 0;GRBVar * *运输= 0;int transportCt = 0; try { // Number of plants and warehouses const int nPlants = 5; const int nWarehouses = 4; // Warehouse demand in thousands of units double Demand[] = { 15, 18, 14, 20 }; // Plant capacity in thousands of units double Capacity[] = { 20, 22, 17, 19, 18 }; // Fixed costs for each plant double FixedCosts[] = { 12000, 15000, 17000, 13000, 16000 }; // Transportation costs per thousand units double TransCosts[][nPlants] = { { 4000, 2000, 3000, 2500, 4500 }, { 2500, 2600, 3400, 3000, 4000 }, { 1200, 1800, 2600, 4100, 3000 }, { 2200, 2600, 3100, 3700, 3200 } }; // Model env = new GRBEnv(); GRBModel model = GRBModel(*env); model.set(GRB_StringAttr_ModelName, "facility"); // Plant open decision variables: open[p] == 1 if plant p is open. open = model.addVars(nPlants, GRB_BINARY); int p; for (p = 0; p < nPlants; ++p) { ostringstream vname; vname << "Open" << p; open[p].set(GRB_DoubleAttr_Obj, FixedCosts[p]); open[p].set(GRB_StringAttr_VarName, vname.str()); } // Transportation decision variables: how much to transport from // a plant p to a warehouse w transport = new GRBVar* [nWarehouses]; int w; for (w = 0; w < nWarehouses; ++w) { transport[w] = model.addVars(nPlants); transportCt++; for (p = 0; p < nPlants; ++p) { ostringstream vname; vname << "Trans" << p << "." << w; transport[w][p].set(GRB_DoubleAttr_Obj, TransCosts[w][p]); transport[w][p].set(GRB_StringAttr_VarName, vname.str()); } } // The objective is to minimize the total fixed and variable costs model.set(GRB_IntAttr_ModelSense, GRB_MINIMIZE); // Production constraints // Note that the right-hand limit sets the production to zero if // the plant is closed for (p = 0; p < nPlants; ++p) { GRBLinExpr ptot = 0; for (w = 0; w < nWarehouses; ++w) { ptot += transport[w][p]; } ostringstream cname; cname << "Capacity" << p; model.addConstr(ptot <= Capacity[p] * open[p], cname.str()); } // Demand constraints for (w = 0; w < nWarehouses; ++w) { GRBLinExpr dtot = 0; for (p = 0; p < nPlants; ++p) { dtot += transport[w][p]; } ostringstream cname; cname << "Demand" << w; model.addConstr(dtot == Demand[w], cname.str()); } // Guess at the starting point: close the plant with the highest // fixed costs; open all others // First, open all plants for (p = 0; p < nPlants; ++p) { open[p].set(GRB_DoubleAttr_Start, 1.0); } // Now close the plant with the highest fixed cost cout << "Initial guess:" << endl; double maxFixed = -GRB_INFINITY; for (p = 0; p < nPlants; ++p) { if (FixedCosts[p] > maxFixed) { maxFixed = FixedCosts[p]; } } for (p = 0; p < nPlants; ++p) { if (FixedCosts[p] == maxFixed) { open[p].set(GRB_DoubleAttr_Start, 0.0); cout << "Closing plant " << p << endl << endl; break; } } // Use barrier to solve root relaxation model.set(GRB_IntParam_Method, GRB_METHOD_BARRIER); // Solve model.optimize(); // Print solution cout << "\nTOTAL COSTS: " << model.get(GRB_DoubleAttr_ObjVal) << endl; cout << "SOLUTION:" << endl; for (p = 0; p < nPlants; ++p) { if (open[p].get(GRB_DoubleAttr_X) > 0.99) { cout << "Plant " << p << " open:" << endl; for (w = 0; w < nWarehouses; ++w) { if (transport[w][p].get(GRB_DoubleAttr_X) > 0.0001) { cout << " Transport " << transport[w][p].get(GRB_DoubleAttr_X) << " units to warehouse " << w << endl; } } } else { cout << "Plant " << p << " closed!" << endl; } } } catch (GRBException e) { cout << "Error code = " << e.getErrorCode() << endl; cout << e.getMessage() << endl; } catch (...) { cout << "Exception during optimization" << endl; } delete[] open; for (int i = 0; i < transportCt; ++i) { delete[] transport[i]; } delete[] transport; delete env; return 0; }
