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Thanks for developing this package. It is so cool.
In this package, the location models are solved by tools that are supported py PuLP (Gurobi, GLPK...). However, when the problem size becomes large, the exact solvers will converge slowly and take a long time. I am interested to know if there is any existing package that solves the location models (e.g. maximum coverage location problem) using heuristics, such as genetic algorithms.
Thank you very much for your suggestions.
The text was updated successfully, but these errors were encountered:
Hi @huanfachen I'm not aware of any packages that can solve these problems out of the box using other approaches like simulated annealing or genetic algorithms.
Hi! I am in the same position, looking for an implementation of a metaheuristic method for a Facility Location Problem. Did you have any luck, @huanfachen. There doesn't seem to be many examples out there. Thanks
Hi Aaron,
Thanks for developing this package. It is so cool.
In this package, the location models are solved by tools that are supported py PuLP (Gurobi, GLPK...). However, when the problem size becomes large, the exact solvers will converge slowly and take a long time. I am interested to know if there is any existing package that solves the location models (e.g. maximum coverage location problem) using heuristics, such as genetic algorithms.
Thank you very much for your suggestions.
The text was updated successfully, but these errors were encountered: