I have an LP problem (linear objective with eq and ineq constraints) in binary variables.
Except for the objective, all the coefficients are integer, mostly in {-1,0,1}. Maybe the objective coeff could be discretized.
I usually use an MI solver (gurobi). Since it solves a moderate problem in my case under a second, I suspect that it may have a special structure that permits employing a different specialized method that will be faster. Can you suggest other methods to solve my problem?
More details in a duplicate question:
https://math.stackexchange.com/questions/4504572/methods-for-binary-linear-programming/4505035
@worldsmithhelper suggests (in the comments) to test a problem on all solvers using
https://neos-server.org/neos/solvers/index.html
I'm considering automating it. I'm using yalmip, which can export the following formats:
https://yalmip.github.io/tags/#export-and-import
This can be wrapped in an XML and sent via a python client (in a loop for each solver):