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 .
Guner, A. R., & Sevkli, M. (2008). A Discrete Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem. Journal of Artificial Evolution and Applications, 2008, 1–9. https://doi.org/10.1155/2008/861512