A Discrete Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem

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 .