A Discrete Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem | Zendy

Ali R. Güner | Zendy; Mehmet Şevkli | Zendy

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A Discrete Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem

Author(s) -

Ali R. Güner,

Mehmet Şevkli

Publication year - 2008

Publication title -

journal of artificial evolution and applications

Language(s) - English

Resource type - Journals

eISSN - 1687-6237

pISSN - 1687-6229

DOI - 10.1155/2008/861512

Subject(s) - metaheuristic , simulated annealing , particle swarm optimization , benchmark (surveying) , mathematical optimization , multi swarm optimization , genetic algorithm , imperialist competitive algorithm , algorithm , swarm behaviour , combinatorial optimization , computer science , parallel metaheuristic , facility location problem , meta optimization , local search (optimization) , mathematics , geography , geodesy

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 .

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