International Journal of Mathematics in Operational Research 杂志-刊鹿论文编译

Robust and stable flexible job shop scheduling with random machine breakdowns: multi-objectives genetic algorithm approach

Abstract:

In this paper, robust and stable scheduling for a flexible job-shop problem with random machine breakdowns has been discussed. A two-stage genetic algorithm is used to generate the predictive schedule. The first stage optimises the primary objective, which minimises the makespan, where all data is considered to be deterministic with no expected disruptions. The second stage optimises two objectives, makespan and stability, function in the presence of random machine breakdowns. For the second stage two different versions of multi-objective genetic algorithm, non-dominated sorting genetic algorithm II and non-dominated ranking genetic algorithm, is used. A simulator is proposed to simulate random machine breakdowns. An experimental study and analysis of variance is conducted to study the results of each multi-objective algorithm and breakdown simulator. The results of their comparison indicate that, non-dominated ranking genetic algorithm (NRGA) performs better and also shows a significant difference between various repair times in the proposed breakdown simulator.

Author Listing： Seyed Mojtaba Sajadi;Azar Alizadeh;Mostafa Zandieh;Fereshteh Tavan

Volume： 14

Pages： 268-289

DOI： 10.1504/IJMOR.2019.10018980

Language： English

Journal： International Journal of Mathematics in Operational Research

International Journal of Mathematics in Operational Research

影响因子：0.0

是否综述期刊：否

是否OA：是

是否预警：不在预警名单内

发行时间：-

ISSN：1757-5850

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收录数据库：Scopus收录

出版国家/地区：-

出版社：Inderscience Publishers

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自引率	0.0%
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偏重研究方向	Decision Sciences-Decision Sciences (all)
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2025年03月发布的2025版	不在预警名单中
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2020年12月发布的2020版	不在预警名单中

JCR分区 WOS分区等级：Q0区

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WOS期刊SCI分区（2021-2022年最新版）

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