Metaheuristic methods in hybrid flow shop scheduling problem

Authors:
F. Choong;S. Phon-Amnuaisuk;M. Y. Alias
Affiliations:
Taylor's University Lakeside Campus, School of Engineering, No. 1, Jalan Taylor's, 47500 Subang Jaya, Selangor, Malaysia;Taylor's University Lakeside Campus, School of Engineering, No. 1, Jalan Taylor's, 47500 Subang Jaya, Selangor, Malaysia;Taylor's University Lakeside Campus, School of Engineering, No. 1, Jalan Taylor's, 47500 Subang Jaya, Selangor, Malaysia
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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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.