期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 38, 期 4, 页码 3563-3573出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2010.08.145
关键词
Genetic algorithm; Flexible job-shop scheduling; Chromosome representation; Initialization
类别
资金
- 863 High Technology Plan Foundation of China [2006AA04Z131]
- National Natural Science Foundation of China [50825503]
- Program for New Century Excellent Talents in University [NCET-08-0232]
In this paper, we proposed an effective genetic algorithm for solving the flexible job-shop scheduling problem (FJSP) to minimize makespan time. In the proposed algorithm, Global Selection (GS) and Local Selection (LS) are designed to generate high-quality initial population in the initialization stage. An improved chromosome representation is used to conveniently represent a solution of the FJSP, and different strategies for crossover and mutation operator are adopted. Various benchmark data taken from literature are tested. Computational results prove the proposed genetic algorithm effective and efficient for solving flexible job-shop scheduling problem. (C) 2010 Elsevier Ltd. All rights reserved.
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