我正在CPLEX上工作，试图找出调度问题。我阅读了IBM的使用手册，并编写了一些代码。但是我不知道为什么我看不到每个变量的值。当我写cplex.exportModel("filename.lp");时，我得到一个空的。lp文件。这样的:
ENCODING=ISO-8859-1
Problem name: IloCplex
Minimize
obj:
End
下面是我的代码:
#include <iostream>
#include <ilcplex/ilocplex.h>
ILOSTLBEGIN
//using namespace std;
/* Definitions */
IloInt varNumber, lowerBound, upperBound, Wmin, Wmax, Dmin, Dmax;
IloIntArray objScalars;
void define_data(IloEnv);
static void populateSomething(IloModel, IloNumVarArray, IloRangeArray);
int main(int argc, char **argv) {
cout << "running.." << endl << endl;
IloEnv env;
try{
IloModel model(env);
IloCplex cplex(model);
IloObjective obj;
IloNumVarArray var(env);
IloRangeArray rng(env);
cplex.exportModel("cplexcpp.lp");
cplex.extract(model);
define_data(env);
populateSomething(model, var, rng);
if(cplex.solve()){
env.out() << "Solution status = " << cplex.getStatus() << endl;
env.out() << "Solution value = " << cplex.getObjValue() << endl;
IloNumArray vals(env);
cplex.getValues(vals, var);
env.out() << "Values = " << vals << endl;
cplex.getSlacks(vals, rng);
env.out() << "Slacks = " << vals << endl;
cplex.getDuals(vals, rng);
env.out() << "Duals = " << vals << endl;
cplex.getReducedCosts(vals, var);
env.out() << "Reduced Costs = " << vals << endl;
}
obj.end();
}catch (IloException& e){
cerr << "Concert exception caught: " << e << endl;
}catch (...){
cerr << "Unknown exception caught: " << endl;
}
env.end();
return 0;
}
/* Initializations */
void define_data(IloEnv env){
varNumber = 20;
lowerBound = 0;
upperBound = 1;
objScalars = IloIntArray(env, varNumber,
10, -1, 8, -1,
16, 18, 20, 14,
-3, 30, -3, -3,
40, -4, -4, 40,
-5, 45, 10, -5
);
Dmin = 0;
Dmax = 10;
Wmin = 10;
Wmax = 25;
}
/*
static void usage(const char *progname){
cerr << "Usage: " << progname << " -X" << endl;
cerr << "Exiting ... " << endl;
}*/
/* Implementation */
static void populateSomething(IloModel model, IloNumVarArray Yijk, IloRangeArray rng){
IloEnv env = model.getEnv();
Yijk = IloNumVarArray(env, varNumber, lowerBound, upperBound, ILOINT);
//IloNumVarArray Xik = IloNumVarArray(env, varNumber, lowerBound, upperBound, ILOINT);
//Objective Function:
model.add(IloMaximize(env, IloScalProd(objScalars, Yijk)));
//Constraint 1-1:
IloExpr expr1(env);
for(IloInt i = 0; i < varNumber; i += 4){
expr1.setLinearCoef(Yijk[i], 1);
}
IloRange rng1 = IloRange(env, 2, expr1, 2);
rng.IloExtractableArray::add(rng1);
expr1.end();
//Constraint 1-2:
IloExpr expr2(env);
for (IloInt i = 1; i < varNumber; i += 4) {
expr2.setLinearCoef(Yijk[i], 1);
}
IloRange rng2 = IloRange(env, 1, expr2, 1);
rng.IloExtractableArray::add(rng2);
expr2.end();
//Constraint 1-3:
IloExpr expr3(env);
for(IloInt i = 2; i < varNumber; i += 4){
expr3.setLinearCoef(Yijk[i], 1);
}
IloRange rng3 = IloRange(env, 1, expr3, 1);
rng.IloExtractableArray::add(rng3);
expr3.end();
//Constraint 1-4:
IloExpr expr4(env);
for(IloInt i = 3; i < varNumber; i += 4){
expr4.setLinearCoef(Yijk[i], 1);
}
IloRange rng4 = IloRange(env, 2, expr4, 2);
rng.IloExtractableArray::add(rng4);
expr4.end();
//Constraint 2:
for(IloInt i = 0; i < varNumber; i += 2){
//IloRange(env, 0, 7 * Yijk[i] + 8 * Yijk[i+1], 10);
rng.add(IloRange(env, Dmin, 7 * Yijk[i] + 8 * Yijk[i+1], Dmax));
}
//Constraint 3:
for(IloInt i = 0; i < varNumber; i += 4){
rng.add(IloRange(env, Wmin, 7 * Yijk[i] + 8 * Yijk[i+1] + 7 * Yijk[i+2] + 8 * Yijk[i+3] ,Wmax));
}
}
运行模型后，结果如下:
Default variable names x1, x2 ... being created.
Default row names c1, c2 ... being created.
THE MODEL :
IloModel model0 = {
obj42 = (10 * IloIntVar(1)[0..1] + -1 * IloIntVar(2)[0..1] + 8 * IloIntVar(3)[0..1] + -1 * IloIntVar(4)[0..1] + 16 * IloIntVar(5)[0..1] + 18 * IloIntVar(6)[0..1] + 20 * IloIntVar(7)[0..1] + 14 * IloIntVar(8)[0..1] + -3 * IloIntVar(9)[0..1] + 30 * IloIntVar(10)[0..1] + -3 * IloIntVar(11)[0..1] + -3 * IloIntVar(12)[0..1] + 40 * IloIntVar(13)[0..1] + -4 * IloIntVar(14)[0..1] + -4 * IloIntVar(15)[0..1] + 40 * IloIntVar(16)[0..1] + -5 * IloIntVar(17)[0..1] + 45 * IloIntVar(18)[0..1] + 10 * IloIntVar(19)[0..1] + -5 * IloIntVar(20)[0..1] , IloObjective, Maximize);
}
THE RNG :
[IloIntVar(1)[0..1] + IloIntVar(5)[0..1] + IloIntVar(9)[0..1] + IloIntVar(13)[0..1] + IloIntVar(17)[0..1] == 2 , IloIntVar(2)[0..1] + IloIntVar(6)[0..1] + IloIntVar(10)[0..1] + IloIntVar(14)[0..1] + IloIntVar(18)[0..1] == 1 , IloIntVar(3)[0..1] + IloIntVar(7)[0..1] + IloIntVar(11)[0..1] + IloIntVar(15)[0..1] + IloIntVar(19)[0..1] == 1 , IloIntVar(4)[0..1] + IloIntVar(8)[0..1] + IloIntVar(12)[0..1] + IloIntVar(16)[0..1] + IloIntVar(20)[0..1] == 2 , 0 <= 7 * IloIntVar(1)[0..1] + 8 * IloIntVar(2)[0..1] <= 10 , 0 <= 7 * IloIntVar(3)[0..1] + 8 * IloIntVar(4)[0..1] <= 10 , 0 <= 7 * IloIntVar(5)[0..1] + 8 * IloIntVar(6)[0..1] <= 10 , 0 <= 7 * IloIntVar(7)[0..1] + 8 * IloIntVar(8)[0..1] <= 10 , 0 <= 7 * IloIntVar(9)[0..1] + 8 * IloIntVar(10)[0..1] <= 10 , 0 <= 7 * IloIntVar(11)[0..1] + 8 * IloIntVar(12)[0..1] <= 10 ,
0 <= 7 * IloIntVar(13)[0..1] + 8 * IloIntVar(14)[0..1] <= 10 , 0 <= 7 * IloIntVar(15)[0..1] + 8 * IloIntVar(16)[0..1] <= 10 , 0 <= 7 * IloIntVar(17)[0..1] + 8 * IloIntVar(18)[0..1] <= 10 , 0 <= 7 * IloIntVar(19)[0..1] + 8 * IloIntVar(20)[0..1] <= 10 , 10 <= 7 * IloIntVar(1)[0..1] + 8 * IloIntVar(2)[0..1] + 7 * IloIntVar(3)[0..1] + 8 * IloIntVar(4)[0..1] <= 25 , 10 <= 7 * IloIntVar(5)[0..1] + 8 * IloIntVar(6)[0..1] + 7 * IloIntVar(7)[0..1] + 8 * IloIntVar(8)[0..1] <= 25 , 10 <= 7 * IloIntVar(9)[0..1] + 8 * IloIntVar(10)[0..1] + 7 * IloIntVar(11)[0..1] + 8 * IloIntVar(12)[0..1] <= 25 , 10 <= 7 * IloIntVar(13)[0..1] + 8 * IloIntVar(14)[0..1] + 7 * IloIntVar(15)[0..1] + 8 * IloIntVar(16)[0..1] <= 25 , 10 <= 7 * IloIntVar(17)[0..1] + 8 * IloIntVar(18)[0..1] + 7 * IloIntVar(19)[0..1] + 8 * IloIntVar(20)[0..1] <= 25 , IloIntVar(1)[0..1] <= IloIntVar(21)[0..1] ,
IloIntVar(2)[0..1] <= IloIntVar(22)[0..1] , IloIntVar(3)[0..1] <= IloIntVar(23)[0..1] , IloIntVar(4)[0..1] <= IloIntVar(24)[0..1] , IloIntVar(5)[0..1] <= IloIntVar(25)[0..1] , IloIntVar(6)[0..1] <= IloIntVar(26)[0..1] , IloIntVar(7)[0..1] <= IloIntVar(27)[0..1] , IloIntVar(8)[0..1] <= IloIntVar(28)[0..1] , IloIntVar(9)[0..1] <= IloIntVar(29)[0..1] , IloIntVar(10)[0..1] <= IloIntVar(30)[0..1] , IloIntVar(11)[0..1] <= IloIntVar(31)[0..1] ,
IloIntVar(12)[0..1] <= IloIntVar(32)[0..1] , IloIntVar(13)[0..1] <= IloIntVar(33)[0..1] , IloIntVar(14)[0..1] <= IloIntVar(34)[0..1] , IloIntVar(15)[0..1] <= IloIntVar(35)[0..1] , IloIntVar(16)[0..1] <= IloIntVar(36)[0..1] , IloIntVar(17)[0..1] <= IloIntVar(37)[0..1] , IloIntVar(18)[0..1] <= IloIntVar(38)[0..1] , IloIntVar(19)[0..1] <= IloIntVar(39)[0..1] , IloIntVar(20)[0..1] <= IloIntVar(40)[0..1] ]
Found incumbent of value 0.000000 after 0.00 sec. (0.00 ticks)
Found incumbent of value 222.000000 after 0.00 sec. (0.00 ticks)
Tried aggregator 1 time.
MIP Presolve eliminated 0 rows and 20 columns.
All rows and columns eliminated.
Presolve time = 0.00 sec. (0.00 ticks)
Root node processing (before b&c):
Real time = 0.00 sec. (0.01 ticks)
Parallel b&c, 4 threads:
Real time = 0.00 sec. (0.00 ticks)
Sync time (average) = 0.00 sec.
Wait time (average) = 0.00 sec.
------------
Total (root+branch&cut) = 0.00 sec. (0.01 ticks)
Solution status = Optimal
Solution value = 251
Values = []
Concert exception caught: IloExtractable 44 IloRangeI has not been extracted by IloAlgorithm 0x101813000
Program ended with exit code: 0
我的目标是得到每一个决策变量的值，要么是1，要么是0。有人知道我的问题是什么吗?我该如何解决这个问题?非常感谢!!
第一个观察，在您向模型添加任何内容之前，您正在导出一个模型。在解决问题之前，请尝试将导出移到。
所以我一直有和你一样的问题，即打印"空"文件。但最近，我遇到了IloCplex::extract方法，显然你必须首先"提取"。你的模型然后"导出"。在我的例子中，下面的代码完成了这个任务:
cplex.extract(model);
cplex.exportModel("recourse.lp");
其中model是我的对象，"recourse.lp"是我的const char * filename