Table of Contents
Journal of Artificial Evolution and Applications
Volume 2008, Article ID 861512, 9 pages
Research Article

A Discrete Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem

1Department of Industrial and Manufacturing Engineering, College of Engineering, Wayne State University, Detroit, MI 48202, USA
2Department of Industrial Engineering, Faculty of Engineering, Fatih University, 34500 Büyükçekmece, Istanbul, Turkey

Received 5 July 2007; Revised 27 December 2007; Accepted 12 March 2008

Academic Editor: T. Blackwell

Copyright © 2008 Ali R. Guner and Mehmet Sevkli. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.