private static double[][] calKnapsackWithLpSolve(double stockLen, double[] orderNumVec, double[] orderLenVec)
{
int nVar = orderNumVec.Length - 1;
IntPtr solver = Lpsolve.make_lp(0, nVar);
Lpsolve.set_verbose(solver, 1);
// add constraints
Lpsolve.add_constraint(solver, orderLenVec, Lpsolve.lpsolve_constr_types.LE, stockLen);
// objArr.length is equal to nCol + 1
for (int c = 1; c <= nVar; c++)
{
Lpsolve.set_int(solver, c, 1);
double[] constraintVec = new double[nVar + 1];
constraintVec[0] = nVar;
for (int cIndex = 1; cIndex <= nVar; cIndex++)
{
constraintVec[cIndex] = cIndex == c ? 1 : 0;
}
Lpsolve.add_constraint(solver, constraintVec, Lpsolve.lpsolve_constr_types.LE, orderNumVec[c]);
}
// set objective function
Lpsolve.set_obj_fn(solver, orderLenVec);
Lpsolve.set_maxim(solver);
// solve the problem
int solFlag = (int)Lpsolve.solve(solver);
// solution
double reducedCost = Lpsolve.get_objective(solver);
double[] var = new double[Lpsolve.get_Ncolumns(solver)];
Lpsolve.get_variables(solver, var);
// delete the problem and free memory
Lpsolve.delete_lp(solver);
// Prepare result
double[][] rst = new double[2][];
rst[0] = new double[] { reducedCost };
rst[1] = var;
return(rst);
}
