[SCIP] SCIP presolve advice

[David Escobar-Vargas, Mr]

Dear SCIP team,

I'm currently working on integrating machine learning into presolve methods for MIPs, specifically focusing on Vehicle Routing Problems (VRPs). I am continuing the work of a previous student who started using SCIP. The initial goal is to use SCIP presolve, gather some statistics for feature selection, and then call a heuristic for solving the MIP of a VRP. I have a bunch of .cip files of VRPs, and I need to read them, use presolve, extract the model after presolve (to get the coefficients from linear/quadratic constraints/objective), solve the resulting MIP with the heuristic, and use SCIP's post-solve to get the solution.

Unfortunately, my colleague did not leave much documentation other than a Python code using PySCIPOpt for model creation and a note mentioning that we need SCIP's C++ wrapper to do the rest.

This is my first time using SCIP. I've spent a couple of days working with SCIP and have managed to use the C-API to read the .cip files, call the presolve, and retrieve some of the linear coefficients in the objectives/constraints. I'm currently using SCIPfindConshdlr and SCIPconsGetHdlr to identify the linear and quadratic constraints, but I still don't know how to get the quadratic coefficients from the objective and constraints.

After this initial experience with SCIP, I would like to ask for your expertise in confirming whether what I am trying to do is feasible with the latest version of SCIP and the C-API, especially considering that I have problems with and without quadratic constraints (and possibly quadratic objectives).

I would greatly appreciate any advice you can share to help me determine if my plan is possible and how to proceed with the project.

Thank you in advance for your support!

Best,


David Escobar Vargas PhD

Senior Algorithms Researcher

Postdoctoral Fellow, Université Laval
Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT)
Montreal, Canada
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