Capacitated facility location: Separation algorithms and computational experience

We consider the polyhedral approach to solving the capacitated facility location problem. The valid inequalities considered are the knapsack, ow cover, e ective capacity, single depot, and combinatorial inequalities. The ow cover, e ective capacity, and single depot inequalities form subfamilies of the general family of submodular inequalities. The separation problem based on the family of submodular inequalities is NP-hard in general. For the well-known subclass of ow cover inequalities, however, we show that if the client set is xed, and if all capacities are equal, then the separation problem can be solved in polynomial time. For the ow cover inequalities based on an arbitrary client set, and for the e ective capacity and single depot inequalities we develop separation heuristics. An important part of all these heuristic is based on constructive proofs that two speci c conditions are necessary for the e ective capacity inequalities to be facet de ning. The proofs show precisely how structures that violate the two conditions can be modi ed to produce stronger inequalities. The family of combinatorial inequalities was originally developed for the uncapacitated facility location problem, but is also valid for the capacitated problem. No computational experience using the combinatorial inequalities has been reported so far. Here we suggest how partial output from the heuristic identifying violated submodular inequalities can be used as input to a heuristic identifying violated combinatorial inequalities. We report on computational results from solving 60 small and medium size problems.