An approach using particle swarm optimization and bottleneck heuristic to solve hybrid flow shop scheduling problem

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• 作者：Ching-Jong Liao ; ^{cjliao@mail.ntust.edu.tw} ; Evi Tjandradjaja ; Tsui-Ping Chung
• 关键词：Hybrid flow shop ; Particle swarm optimization ; Bottleneck heuristic ; Simulated annealing ; Scheduling
• 刊名：Applied Soft Computing Journal
• 出版年：2012
• 期刊代码：9_15684946
• 类别：cp
• 出版时间：June, 2012
• 卷：12
• 期：6
• 页码：1755-1764
• 文件大小：408 K

摘要

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 N茅ron. Experimental results show that the proposed algorithm outperforms all the compared algorithms in solving the HFS problem.