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论文类型：期刊论文

发表时间：2010-10-01

发表刊物：JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY

收录刊物：SCIE、EI、Scopus

卷号：24

期号：10

页面范围：2119-2125

ISSN号：1738-494X

关键字：FJSP; GA; Coding rules; Decoding algorithm

摘要：Aiming at the existing problems with GA (genetic algorithm) for solving a flexible job-shop scheduling problem (FJSP), such as description model disunity, complicated coding and decoding methods, a FJSP solution method based on GA is proposed in this paper, and job-shop scheduling problem (JSP) with partial flexibility and JIT Oust-in-time) request is transformed into a general FJSP. Moreover, a unified mathematical model is given. Through the improvement of coding rules, decoding algorithm, crossover and mutation operators, the modified GA's convergence and search efficiency have been enhanced. The example analysis proves the proposed methods can make FJSP converge to the optimal solution steadily, exactly, and efficiently.