一、涉及软件
Visual Studio 2017、Visual Studio 2019
CPLEX 12.9.0
二、配置效果
1、可以实现C++调用CPLEX求解线性规划，混合整数规划等；
2、可以在debug和release两种模式下进行调试或者运行代码
三、配置步骤
1、首先选择代码运行的环境
(1)、将平台设置为x64或者(活动)x64，此处一定需要修改！不能使用x32平台模式
(2)、配置的设置可以根据需要自行选择release模式或者debug模式（作者建议两种都进行配置一下，方便后续使用）
2、打开项目的属性项
3、修改C/C++附加包含目录
这里找到CPLEX的安装目录(根据自己的安装目录进行修改)，如本人的是：
(注：下述若不做特殊说明，均需要将目录替换为自己的目录，若安装时没进行修改，从IBM/ILOG/…的目录同下述目录应该相同)
//CPLEX安装目录 D:\Program Files\IBM\ILOG\CPLEX_Studio129\concert\include D:\Program Files\IBM\ILOG\CPLEX_Studio129\cplex\include •
将上述两项加入到附加目录之中，点击确定，效果如下：
4、修改C/C++预处理器中的预处理器定义项
添加下述命令到预处理器定义中（此处无需进行修改，直接复制粘贴就好）：
NDEBUG _CONSOLE IL_STD
5、修改C/C++代码生成中的运行库
将此处的改为多线程DLL(/MD)或者多线程调试DLL(/MDd)
6、修改链接器常规项中的“附加库目录项”
将下述两个目录添加到“附加库目录项”中，目录地址同上述CPLEX安装目录相同
D:\Program Files\IBM\ILOG\CPLEX_Studio129\concert\lib\x64_windows_vs2017\stat_mda D:\Program Files\IBM\ILOG\CPLEX_Studio129\cplex\lib\x64_windows_vs2017\stat_mda
7、修改链接器输入中的“附加依赖项”
将下述两个目录添加到“附加库目录项”中，目录地址同上述CPLEX安装目录相同
D:\Program Files\IBM\ILOG\CPLEX_Studio129\concert\lib\x64_windows_vs2017\stat_mda\concert.lib D:\Program Files\IBM\ILOG\CPLEX_Studio129\cplex\lib\x64_windows_vs2017\stat_mda\cplex1290.lib D:\Program Files\IBM\ILOG\CPLEX_Studio129\cplex\lib\x64_windows_vs2017\stat_mda\ilocplex.lib
8、 点击确定，点击应用，大功告成！
四、运行测试代码
1、下面给出CPLEX官方测试文档中的cutstock代码进行测试
#include <ilcplex/ilocplex.h> ILOSTLBEGIN #define RC_EPS 1.0e-6 static void readData(const char* filename, IloNum& rollWidth, IloNumArray& size, IloNumArray& amount); static void report1(IloCplex& cutSolver, IloNumVarArray Cut, IloRangeArray Fill); static void report2(IloAlgorithm& patSolver, IloNumVarArray Use, IloObjective obj); static void report3(IloCplex& cutSolver, IloNumVarArray Cut); /// MAIN PROGRAM /// int main(int argc, char **argv) { IloEnv env; try { IloInt i, j; IloNum rollWidth; IloNumArray amount(env); IloNumArray size(env); if (argc > 1) readData(argv[1], rollWidth, size, amount); else readData("cutstock.dat", rollWidth, size, amount); /// CUTTING-OPTIMIZATION PROBLEM /// IloModel cutOpt(env); IloObjective RollsUsed = IloAdd(cutOpt, IloMinimize(env)); IloRangeArray Fill = IloAdd(cutOpt, IloRangeArray(env, amount, IloInfinity)); IloNumVarArray Cut(env); IloInt nWdth = size.getSize(); for (j = 0; j < nWdth; j++) { Cut.add(IloNumVar(RollsUsed(1) + Fill[j](int(rollWidth / size[j])))); } IloCplex cutSolver(cutOpt); /// PATTERN-GENERATION PROBLEM /// IloModel patGen(env); IloObjective ReducedCost = IloAdd(patGen, IloMinimize(env, 1)); IloNumVarArray Use(env, nWdth, 0.0, IloInfinity, ILOINT); patGen.add(IloScalProd(size, Use) <= rollWidth); IloCplex patSolver(patGen); /// COLUMN-GENERATION PROCEDURE /// IloNumArray price(env, nWdth); IloNumArray newPatt(env, nWdth); /// COLUMN-GENERATION PROCEDURE /// for (;;) { /// OPTIMIZE OVER CURRENT PATTERNS /// cutSolver.solve(); report1(cutSolver, Cut, Fill); /// FIND AND ADD A NEW PATTERN /// for (i = 0; i < nWdth; i++) { price[i] = -cutSolver.getDual(Fill[i]); } ReducedCost.setLinearCoefs(Use, price); patSolver.solve(); report2(patSolver, Use, ReducedCost); if (patSolver.getValue(ReducedCost) > -RC_EPS) break; patSolver.getValues(newPatt, Use); Cut.add(IloNumVar(RollsUsed(1) + Fill(newPatt))); } cutOpt.add(IloConversion(env, Cut, ILOINT)); cutSolver.solve(); cout << "Solution status: " << cutSolver.getStatus() << endl; report3(cutSolver, Cut); } catch (IloException& ex) { cerr << "Error: " << ex << endl; } catch (...) { cerr << "Error" << endl; } env.end(); return 0; } static void readData(const char* filename, IloNum& rollWidth, IloNumArray& size, IloNumArray& amount) { ifstream in(filename); if (in) { in >> rollWidth; in >> size; in >> amount; } else { cerr << "No such file: " << filename << endl; throw(1); } } static void report1(IloCplex& cutSolver, IloNumVarArray Cut, IloRangeArray Fill) { cout << endl; cout << "Using " << cutSolver.getObjValue() << " rolls" << endl; cout << endl; for (IloInt j = 0; j < Cut.getSize(); j++) { cout << " Cut" << j << " = " << cutSolver.getValue(Cut[j]) << endl; } cout << endl; for (IloInt i = 0; i < Fill.getSize(); i++) { cout << " Fill" << i << " = " << cutSolver.getDual(Fill[i]) << endl; } cout << endl; } static void report2(IloAlgorithm& patSolver, IloNumVarArray Use, IloObjective obj) { cout << endl; cout << "Reduced cost is " << patSolver.getValue(obj) << endl; cout << endl; if (patSolver.getValue(obj) <= -RC_EPS) { for (IloInt i = 0; i < Use.getSize(); i++) { cout << " Use" << i << " = " << patSolver.getValue(Use[i]) << endl; } cout << endl; } } static void report3(IloCplex& cutSolver, IloNumVarArray Cut) { cout << endl; cout << "Best integer solution uses " << cutSolver.getObjValue() << " rolls" << endl; cout << endl; for (IloInt j = 0; j < Cut.getSize(); j++) { cout << " Cut" << j << " = " << cutSolver.getValue(Cut[j]) << endl; } }
2、首先编译代码，出现下面截图说明配置成功辽
3、给出输入文件信息如下：
115 [25, 40, 50, 55, 70] [50, 36, 24, 8, 30]
4、运行结果如下：
