A simple and effective genetic algorithm for the two-stage capacitated facility location problem

• We propose a genetic algorithm to approach a two-stage facility location problem.
• The proposed algorithm outperforms two state-of-the-art Lagrangian heuristics.
• In the worst tested case, the algorithm is at most 1.10% from the optimum solution.

This paper presents a simple and effective Genetic Algorithm (GA) for the two-stage capacitated facility location problem (TSCFLP). The TSCFLP is a typical location problem which arises in freight transportation. In this problem, a single product must be transported from a set of plants to meet customers demands, passing out by intermediate depots. The objective is to minimize the operation costs of the underlying two-stage transportation system thereby satisfying demand and capacity constraints of its agents. For this purpose, a GA is proposed and computational results are reported comparing the heuristic results with those obtained by two state-of-the-art Lagrangian heuristics proposed in the literature for the problem.