Title: Hybrid Simulated Annealing in Flow Shop Scheduling: a diversification and intensification approach

Authors: Nader Azizi, Ming Liang, Saeed Zolfaghari

Addresses: Department of Mechanical Engineering, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada. ' Department of Mechanical Engineering, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada. ' Department of Mechanical and Industrial Engineering, Ryerson University, 350 Victoria Street, Toronto, Ontario, M5B 2K3, Canada

Abstract: In the last few decades, several effective algorithms to solve combinatorial problems have been proposed. However, the challenging nature of these problems restricts the effectiveness of the conventional techniques. This paper presents a generic framework, SAMED, to tackle combinatorial optimisation problems. Based on this framework, a new algorithm tailored for Flow Shop Scheduling, SAMED-FSS, has been developed. The performance of the proposed method has been compared with other techniques including a conventional simulated annealing, a standard genetic algorithm, and a hybrid genetic algorithm. The computational results clearly indicate that the proposed algorithm is much more efficient than the conventional heuristics.

Keywords: evolution based diversification; FSS; flow shop scheduling; GAs; genetic algorithms; simulated annealing; tabu search; combinatorial optimisation.

DOI: 10.1504/IJISE.2009.023545

International Journal of Industrial and Systems Engineering, 2009 Vol.4 No.3, pp.326 - 348

Published online: 27 Feb 2009 *

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