A continuous particle swarm optimization algorithm for uncapacitated facility location problem

Authors:
Mehmet Sevkli;Ali R. Guner
Affiliations:
Department of Industrial Engineering, Fatih University, Istanbul, Turkey;Department of Industrial and Manufacturing Engineering, Wayne State University, Detroit, MI
Venue:
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Year:
2006

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Abstract

In this paper, a continuous Particle Swarm Optimization (PSO) algorithm is presented for the Uncapacitated Facility Location (UFL) problem. In order to improve the solution quality a local search is embedded to the PSO algorithm. It is applied to several benchmark suites collected from OR-library. The results are presented and compared to the results of two recent metaheuristic approaches, namely Genetic Algorithm(GA) and Evolutionary Simulated Annealing (ESA). It is concluded that the PSO algorithm is better than the compared methods and generates more robust results.