Does anyone know what the state of the art industry solvers do for these problems? I had dabbled a bit in ml approaches to combinatorial optimization with great interest a few years back, but I don't think any of these rl based methods ended up being used in production.
The state of the art solvers are the proprietary ones like Gurobi, FICO, Cplex, Mosek, etc. A major contributor to the proprietary "sauce" is in the heuristics they use. For example, all solvers will have a "presolve" phase which attempts to eliminate redundant constraints/variables. There may be some ML they are using behind the scenes to derive these heuristics, I'm not sure, although I know it is a major research area.
Otherwise, the basic underlying algorithms are all the same, as in the textbook: branch-and-bound and so on.
