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For MIP and LP I have used CPLEX, Gurobi and to a lesser extent Cbc. I used those three using JuMP (Julia package for mathematical programming) and Gurobi via pulp and pyomo. Of all three, I think Gurobi has a very accessible documentation, note that I am not saying better or more complete which in that case it would go to CPLEX, and the integration with Python straight out of the box is very useful. Cbc is a lifesaver when we couldn't access the academic licenses of the other two. Overall, I think CPLEX/Gurobi are my favorites with a slight edge to Gurobi. I have tried formulating problems using .lp and GAMS but JuMP is so much more ergonomic even if it's strictly tied to Julia (which I find to be a good thing).



I used Gurobi for logistics routing problems years ago and loved it. Especially loved that I could get a fully functional trial that was limited by total variables to develop my problem and use the license version for the production problems


For open-source, the HiGHS MIP solver vastly out-performs Cbc now, and is easily called from JuMP




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