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by mccourt
3600 days ago
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Yeah, I think that's probably the split - folks from computer science/discrete math on one side and folks from engineering on the other. I grew up in math, but I was on the numerical analysis side so I definitely ended up on the MINLP side, which is why that's what I generally reference. There is certainly something elegant about ILP problems which gets lost when treating them with the sledgehammer that is gradient-based convex optimization. |
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It is funny that you call gradient-based convex optimization a "sledgehammer" since people working in combinatorial optimization (opposed to ILP) tend to denote ILP methods (e.g. cutting plane algorithms, branch & bound, branch & cut, relaxation hierarchies, ...) also as a "sledgehammer". :-D They are just jealous. :-)