Proposing an integrated genetic algorithm for solving job-oriented multi-objective FJSP

Xiuli Wu; Shudong Sun; Zhan Yang; Zhiqiang Cai

Proposing an integrated genetic algorithm for solving job-oriented multi-objective FJSP

Xiuli Wu
, Shudong Sun
, Zhan Yang
, Zhiqiang Cai

机电学院

Northwestern Polytechnical University Xian

科研成果: 期刊稿件 › 文章 › 同行评审

4 引用（Scopus）

摘要

We propose an integrated genetic algorithm that can solve Job-oriented multi-objective FJSP (Flexible Job Shop Scheduling Problem) better. Scheduling model and job-oriented multi-objective algorithm for optimizing the solution of job-oriented multi-objective FJSP are proposed. We give a numerical simulation example, whose results are given in Tables 1 through 3 in the full paper and shown in Fig.2 of the full paper giving the Gantt chart of the best-compromise solution. These results show preliminarily that the proposed algorithm can solve job-oriented multi-objective FJSP efficiently and effectively.

源语言	英语
页（从-至）	477-481
页数	5
期刊	Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
卷	24
期	4
出版状态	已出版 - 8月 2006

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abstract = "We propose an integrated genetic algorithm that can solve Job-oriented multi-objective FJSP (Flexible Job Shop Scheduling Problem) better. Scheduling model and job-oriented multi-objective algorithm for optimizing the solution of job-oriented multi-objective FJSP are proposed. We give a numerical simulation example, whose results are given in Tables 1 through 3 in the full paper and shown in Fig.2 of the full paper giving the Gantt chart of the best-compromise solution. These results show preliminarily that the proposed algorithm can solve job-oriented multi-objective FJSP efficiently and effectively.",

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author = "Xiuli Wu and Shudong Sun and Zhan Yang and Zhiqiang Cai",

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T1 - Proposing an integrated genetic algorithm for solving job-oriented multi-objective FJSP

AU - Wu, Xiuli

AU - Sun, Shudong

AU - Yang, Zhan

AU - Cai, Zhiqiang

PY - 2006/8

Y1 - 2006/8

N2 - We propose an integrated genetic algorithm that can solve Job-oriented multi-objective FJSP (Flexible Job Shop Scheduling Problem) better. Scheduling model and job-oriented multi-objective algorithm for optimizing the solution of job-oriented multi-objective FJSP are proposed. We give a numerical simulation example, whose results are given in Tables 1 through 3 in the full paper and shown in Fig.2 of the full paper giving the Gantt chart of the best-compromise solution. These results show preliminarily that the proposed algorithm can solve job-oriented multi-objective FJSP efficiently and effectively.

AB - We propose an integrated genetic algorithm that can solve Job-oriented multi-objective FJSP (Flexible Job Shop Scheduling Problem) better. Scheduling model and job-oriented multi-objective algorithm for optimizing the solution of job-oriented multi-objective FJSP are proposed. We give a numerical simulation example, whose results are given in Tables 1 through 3 in the full paper and shown in Fig.2 of the full paper giving the Gantt chart of the best-compromise solution. These results show preliminarily that the proposed algorithm can solve job-oriented multi-objective FJSP efficiently and effectively.

KW - Integrated genetic algorithm

KW - Job-oriented multi-objective FJSP (Flexible Job Shop Scheduling Problem)

UR - https://www.scopus.com/pages/publications/33750900083

M3 - 文章

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SN - 1000-2758

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EP - 481

JO - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University

JF - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University

IS - 4

ER -

Proposing an integrated genetic algorithm for solving job-oriented multi-objective FJSP

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