Metaheuristic methods in hybrid flow shop scheduling problem |
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| Authors: | F Choong S Phon-Amnuaisuk MY Alias |
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| Affiliation: | 1. Departamento de Organización de Empresas, Universitat Politècnica de València, Camino de Vera s/n, 46021 València, Spain;2. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad, Grupo de Sistemas de Optimización Aplicada, Instituto Tecnológico de Informática, Ciudad Politécnica de la Innovación, Edifico 8G, Acc. B. Universitat Politècnica de València, Camino de Vera s/n, 46021 València, Spain;1. Dipartimento di Ingegneria Industriale e Meccanica, University of Catania, Viale Andrea Doria 6, 95125 Catania, Italy;2. Dipartimento di Ingegneria Elettrica Elettronica e Informatica, University of Catania, Viale Andrea Doria 6, 95125 Catania, Italy;1. Department of Mechanical Engineering, Kamaraj College of Engineering and Technology, Virudhunagar, Tamilnadu 626001, India;2. Department of Mechanical Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamilnadu 626005, India;3. School of Science and Technology, Middlesex University, London NW4 4BT, UK |
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| Abstract: | Memetic algorithms are hybrid evolutionary algorithms that combine global and local search by using an evolutionary algorithm to perform exploration while the local search method performs exploitation. This paper presents two hybrid heuristic algorithms that combine particle swarm optimization (PSO) with simulated annealing (SA) and tabu search (TS), respectively. The hybrid algorithms were applied on the hybrid flow shop scheduling problem. Experimental results reveal that these memetic techniques can effectively produce improved solutions over conventional methods with faster convergence. |
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