A discrete particle swarm optimization algorithm for uncapacitated facility location problem

Authors:
Ali R. Guner;Mehmet Sevkli
Affiliations:
Department of Industrial and Manufacturing Engineering, College of Engineering, Wayne State University, Detroit, MI;Department of Industrial and Manufacturing Engineering, College of Engineering, Wayne State University, Detroit, MI
Venue:
Journal of Artificial Evolution and Applications - Particle Swarms: The Second Decade
Year:
2008

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Abstract

A discrete version of particle swarm optimization (DPSO) is employed to solve uncapacitated facility location (UFL) problem which is one of the most widely studied in combinatorial optimization. In addition, a hybrid version with a local search is defined to get more efficient results. The results are compared with a continuous particle swarm optimization (CPSO) algorithm and two other metaheuristics studies, namely, genetic algorithm (GA) and evolutionary simulated annealing (ESA). To make a reasonable comparison, we applied to same benchmark suites that are collected from OR-library. In conclusion, the results showed that DPSO algorithm is slightly better than CPSO algorithm and competitive with GA and ESA.