Search Strategies for MIP solver OR-tools in Python

Question

I'm currently solving a shift assignment problem in OR-tools in Python, using a MIP solver, one employee at a time. For each seperate problem there is one employee and around 100 shifts. There are a lot of variables and constraints (few 1000's per employee). I've already looked in detail on how to improve each constraint, but no luck. Since the performance is really important, I wanted to further investigate the possibilities to adjust the search strategies, but no luck either. It seems that the documentation is sparse.

Can anyone help me by giving me some options to look into?

This is the solver I'm using:

pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING

Thank you in advance. Let me know if there is any information I need to add here.

Answer 1

You are out of luck. There are no customisation available for the search through the linear solver wrapper.

I would suggest using the CP-SAT for this. You can have a look at:

https://github.com/google/or-tools/blob/master/examples/python/shift_scheduling_sat.py