基于遗传算法的蜂窝式制造系统调度

R. Lorenzo, S. Fichera, V. Grasso
{"title":"基于遗传算法的蜂窝式制造系统调度","authors":"R. Lorenzo, S. Fichera, V. Grasso","doi":"10.1109/KES.1998.725961","DOIUrl":null,"url":null,"abstract":"The flexible manufacturing cell scheduling problem is considered with a multi-objective approach, pursuing together makespan minimisation and the in process job wait minimisation. The formulation of the scheduling problem is discussed, analysing how to generate well suited sequences, like generalised permutation sequences, and the proper construction of a JIT timing of activities. An evolutionary sequencing algorithm based on both classic genetic operators and hybrid operators is then proposed. The hybrid operators have been introduced to construct highly fit initial population, to perform periodically a local search on the population and to maintain enough genetical diversity in the actual population. Simulation runs on a large number of randomly generated problems, showed the high performance of the proposed evolutionary hybrid algorithm, in front of a modified NEH algorithm, in the determination of schedules minimising makespan and in process job wait together.","PeriodicalId":394492,"journal":{"name":"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Scheduling a cellular manufacturing system with GA\",\"authors\":\"R. Lorenzo, S. Fichera, V. Grasso\",\"doi\":\"10.1109/KES.1998.725961\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The flexible manufacturing cell scheduling problem is considered with a multi-objective approach, pursuing together makespan minimisation and the in process job wait minimisation. The formulation of the scheduling problem is discussed, analysing how to generate well suited sequences, like generalised permutation sequences, and the proper construction of a JIT timing of activities. An evolutionary sequencing algorithm based on both classic genetic operators and hybrid operators is then proposed. The hybrid operators have been introduced to construct highly fit initial population, to perform periodically a local search on the population and to maintain enough genetical diversity in the actual population. Simulation runs on a large number of randomly generated problems, showed the high performance of the proposed evolutionary hybrid algorithm, in front of a modified NEH algorithm, in the determination of schedules minimising makespan and in process job wait together.\",\"PeriodicalId\":394492,\"journal\":{\"name\":\"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)\",\"volume\":\"147 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KES.1998.725961\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KES.1998.725961","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

采用多目标方法研究柔性制造单元调度问题,同时追求最大完工时间和在制品等待时间的最小化。讨论了调度问题的表述,分析了如何生成适合的序列,如广义置换序列,以及如何构造活动的JIT定时。然后提出了一种基于经典遗传算子和混合遗传算子的进化排序算法。引入杂交算子来构造高度拟合的初始群体,对群体进行周期性的局部搜索,并在实际群体中保持足够的遗传多样性。在大量随机生成的问题上进行了仿真,结果表明,在改进的NEH算法面前,所提出的进化混合算法在确定调度、最小化完工时间和进程中作业等待方面具有较高的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scheduling a cellular manufacturing system with GA
The flexible manufacturing cell scheduling problem is considered with a multi-objective approach, pursuing together makespan minimisation and the in process job wait minimisation. The formulation of the scheduling problem is discussed, analysing how to generate well suited sequences, like generalised permutation sequences, and the proper construction of a JIT timing of activities. An evolutionary sequencing algorithm based on both classic genetic operators and hybrid operators is then proposed. The hybrid operators have been introduced to construct highly fit initial population, to perform periodically a local search on the population and to maintain enough genetical diversity in the actual population. Simulation runs on a large number of randomly generated problems, showed the high performance of the proposed evolutionary hybrid algorithm, in front of a modified NEH algorithm, in the determination of schedules minimising makespan and in process job wait together.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信