Hello,
First of all thanks for all the effort that has been put into GLPK, it seems like a great project.
For a University project, we try to solve the following problem. Given a RxC matrix M, with all values in [0,1], find a set of D rows that minimizes:
sum_{i=1 .. C} min(M[j][i]) with j in D.
It can be seen that an reasonable upper bound for this problem is (R choose D) * C), and that the problem is in fact linear in both R and C. However, even for small problem instances (D=1, R=25, D=256) the MIP solver already takes 14 seconds; setting the parameters higher results in incredibly high runtimes.
Is there something that should be taken into consideration? Could this be a problem with the GLPK solver?
Attached is a MWE in Python (using the pulp interface).
Best,
Jan
pulp_mwe.py