An approach using particle swarm optimization and bottleneck heuristic to solve hybrid flow shop scheduling problem |
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| Authors: | Ching-Jong Liao Evi Tjandradjaja Tsui-Ping Chung |
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| Affiliation: | 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 Industrial Engineering, Bu-Ali Sina University, Hamedan, Iran;2. Department of Industrial Engineering, Payame Noor University, Tehran, Iran;3. Department of Industrial Engineering, University of Tehran, Tehran, Iran;1. School of Automation, Wuhan University of Technology, Wuhan 430070, Hubei Province, PR China;2. School of Economic and Management, Southwest Jiaotong University, Chengdu, Sichuan Province, PR China |
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| Abstract: | Hybrid flow shops (HFS) are common manufacturing environments in many industries, such as the glass, steel, paper and textile industries. In this paper, we present a particle swarm optimization (PSO) algorithm for the HFS scheduling problem with minimum makespan objective. The main contribution of this paper is to develop a new approach hybridizing PSO with bottleneck heuristic to fully exploit the bottleneck stage, and with simulated annealing to help escape from local optima. The proposed PSO algorithm is tested on the benchmark problems provided by Carlier and Néron. Experimental results show that the proposed algorithm outperforms all the compared algorithms in solving the HFS problem. |
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