Hi all,
I have a MILP problem in GLPK, using CVXPy library. GLPK quickly finds a primary solution (optimal but not integer). But when GLPK switches to branch-and-cut to find an optimal integer solution, it moves very slowly. The main reason is
that GLPK does not find any feasible integer solution after many iterations (see the below log). I can use a simple heuristic algorithm to find an initial feasible and integer solution, which can help GLPK to quickly eliminate non-optimal branches. I am wondering
if there is any way to feed this initial feasible integer solution to GLPK, or its objective value?
Thanks in advance for your time and kind reply.
Sid
[2021/09/08-22:33:43.822] - + 23315: mip = not found yet >= -4.226425346e+08 (3161; 0)
[2021/09/08-22:33:49.082] - + 23327: mip = not found yet >= -4.226425346e+08 (3173; 0)
[2021/09/08-22:33:54.333] - + 23339: mip = not found yet >= -4.226425346e+08 (3185; 0)
[2021/09/08-22:33:59.576] - + 23351: mip = not found yet >= -4.226425346e+08 (3197; 0)
[2021/09/08-22:34:04.615] - + 23364: mip = not found yet >= -4.226425346e+08 (3209; 0)
[2021/09/08-22:34:09.624] - + 23379: mip = not found yet >= -4.226425346e+08 (3221; 0)
[2021/09/08-22:34:14.758] - + 23400: mip = not found yet >= -4.226425346e+08 (3233; 0)
[2021/09/08-22:34:20.118] - + 23417: mip = not found yet >= -4.226425346e+08 (3246; 0)