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SCIP, GLPK.

I don't mind the overhead in developer time. Once you 'git gud' at translating problems to MIP/ LP, it's just a matter of learning syntax. The real trick is in translating problems.

It's a shame more CS courses don't focus on this problem translation meta-algorithm. You can get it in tough theory courses with problem mapping to prove complexity, but its usefulness goes way, way beyond that somewhat niche application. Learning to model problems as max flow, graph partitioning / matching, LP, MIP, gives you absolute super powers way, way beyond what you'd gain by having a solver that's easier to work with.




That skill can be learned, in part, by taking OR-related business administration classes. Some supply chain management courses I looked into were about learning about standard problems (say, travelling salesman problem) and being able to formulate constraints to extend them. Not very theoretical, but useful in practice.




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