I have a huge mps file and would like to get the associated MIP model, i.e., the objective, constraint, and bounds. Is there any tools that could get that?


2 Answers 2


You can use PuLp's import and export functions (this is Python).

For example, the following snippet shows you how to import an mps file and print the corresponding MIP:

var1, prob1 = LpProblem.fromMPS("test.mps")
# {'x': x, 'y': y, 'z': z}
# test_export_dict_MIP:
# 1*x + 4*y + 9*z + 0
# c1: x + y <= 5
# c2: x + z >= 10
# c3: - y + z = 7.5
# x <= 4 Continuous
# -1 <= y <= 1 Continuous
# 0 <= z Integer
  • $\begingroup$ Thanks for the quick response! $\endgroup$ Sep 20, 2021 at 14:59

Virtually any IP solver can do this for you (Cplex/Gurobi/Xpress/...). The general approach would be to:

  1. Import the MPS file into the solver
  2. Export the model in LP format

Note that the above can be accomplished, either programmatically, or through a command-line interface that most solvers provide. As per example, in Cplex you could simply use the Interactive optimizer:

> read my_mip_model.mps
> write my_mip_model.lp

Gurobi and Xpress have similar capabilities (command line syntax is slightly different).

  • 1
    $\begingroup$ @Afshin Oroojlooy, additionally, by using SCIP's interactive shell you are being able to translate that into a specific algebraic language such as GAMS. Then it would be converted to others like AMPL, etc. The command-line codes are: read -> write -> problem -> "modelname".lp,gms,mps, ...; $\endgroup$
    – A.Omidi
    Sep 20, 2021 at 19:52
  • $\begingroup$ Thanks for the tips. I converted the mps file with pulp, but still it is so huge and I cannot figure out what the constraint mean for that instant. Is it possible to get an compact version like those that we use to pass a huge model by reading coefficients from a file? like the syntax that we use in GAMS, Ample, etc.? $\endgroup$ Sep 21, 2021 at 0:21
  • $\begingroup$ As far as I know it is possible. $\endgroup$
    – A.Omidi
    Sep 21, 2021 at 2:53
  • $\begingroup$ That is impossible. How should you for instance deduce the underlying meaning of x+y<=1 without knowing the context of the model. $\endgroup$ Sep 21, 2021 at 10:23
  • 1
    $\begingroup$ That is precisely my point. $\endgroup$ Sep 22, 2021 at 5:02

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