A high performing metaheuristic for job shop scheduling with sequence-dependent setup times |
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Authors: | B. Naderi S.M.T. Fatemi Ghomi M. Aminnayeri |
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Affiliation: | 1. School of Industrial and Systems Engineering, Georgia Institute of Technology, 765 Ferst Drive, Atlanta, GA 30332, USA;2. School of Aerospace Engineering, Georgia Institute of Technology, 270 Ferst Drive, Atlanta, GA 30332, USA;1. Department of Management Science and Engineering, Economics and Management School, Wuhan University, Wuhan, China;2. Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong |
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Abstract: | This paper investigates scheduling job shop problems with sequence-dependent setup times under minimization of makespan. We develop an effective metaheuristic, simulated annealing with novel operators, to potentially solve the problem. Simulated annealing is a well-recognized algorithm and historically classified as a local-search-based metaheuristic. The performance of simulated annealing critically depends on its operators and parameters, in particular, its neighborhood search structure. In this paper, we propose an effective neighborhood search structure based on insertion neighborhoods as well as analyzing the behavior of simulated annealing with different types of operators and parameters by the means of Taguchi method. An experiment based on Taillard benchmark is conducted to evaluate the proposed algorithm against some effective algorithms existing in the literature. The results show that the proposed algorithm outperforms the other algorithms. |
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