A cross entropy-based metaheuristic algorithm for large-scale capacitated facility location problems

• Published in: The Journal of the Operational Research Society Vol. 60; no. 10; pp. 1439 - 1448
• Main Authors: Caserta, M, Quiñonez Rico, E
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis 01.10.2009; Palgrave Macmillan; Palgrave Macmillan UK; Taylor & Francis Ltd
• Subjects: Algorithms; Applied sciences; Approximation; Business and Management; Cost functions; cross entropy; Entropy; Exact sciences and technology; Fixed costs; Flows in networks. Combinatorial problems; Heuristic; Heuristics; Integer programming; local search; location; Location analysis; Logistics; Management; Mathematical vectors; Objective functions; Operational research and scientific management; Operational research. Management science; Operations research; Operations Research/Decision Theory; Optimal solutions; Savings; Studies; Theoretical Paper; Theoretical Papers; Transportation; location; heuristics; integer programming; cross entropy; local search; Local search; Entropy; Location problem; Facility location; Integer programming; Heuristic method; Capacity constraint; Robustness; Large scale; Metamodel
• ISSN: 0160-5682; 1476-9360
• DOI: 10.1057/jors.2008.77

In this paper, we present a metaheuristic-based algorithm for the capacitated facility location problem. The proposed scheme is made up by three phases: (i) solution construction phase, in which a cross entropy-based scheme is used to 'intelligently' guess which facilities should be opened; (ii) local search phase, aimed at exploring the neighbourhood of 'elite' solutions of the previous phase; and (iii) learning phase, aimed at fine-tuning the stochastic parameters of the algorithm. The algorithm has been thoroughly tested on large-scale random generated instances as well as on benchmark problems and computational results show the effectiveness and robustness of the algorithm.