I have tried to use GLPK to solve some large MILP problems, but without much success. The glpk-20.lp file at


when solved give a final solution that is not feasible, although one exists. Is there some way to coax some parameters of GLPK or the problem itself to get an optimal feasible solution of such large MILP problem?

Is the size of such a problem beyond the capability of the MILP solver of GLPK?

Even after doing some modifications such as reducing the coefficients of the objective function, or replacing the value 30000 to 300 in the constraints, no feasible solution could be obtained. I do not see any scaling that would make the GLPK solver find an optimal feasible solution.

It appears that GLPK MILP searching strategy concedes too early to a solution that does not satisfy the constraints although reaching the maximum possible value of the objective function.

Thank you.

-- Mario Latendresse

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