Genetic algorithms for a single-machine multiple orders per job scheduling problem with a common due date

Jens Rocholl, L. Mönch
{"title":"Genetic algorithms for a single-machine multiple orders per job scheduling problem with a common due date","authors":"Jens Rocholl, L. Mönch","doi":"10.1109/COASE.2017.8256240","DOIUrl":null,"url":null,"abstract":"In this paper, we discuss a multiple orders per job (MOJ) scheduling problem. Front opening unified pods (FOUPs) transfer wafers in 300-mm wafer fabs. Several orders can be grouped in one FOUP which can be considered as a job. A lot processing environment is assumed. All the orders have an unrestrictively late common due date. The earliness and tardiness of the orders is minimized. Since the problem is NP-hard, we propose two hybridized genetic algorithms. Computational experiments on randomly generated problem instances are carried out that demonstrate that the genetic algorithms perform well.","PeriodicalId":445441,"journal":{"name":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COASE.2017.8256240","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In this paper, we discuss a multiple orders per job (MOJ) scheduling problem. Front opening unified pods (FOUPs) transfer wafers in 300-mm wafer fabs. Several orders can be grouped in one FOUP which can be considered as a job. A lot processing environment is assumed. All the orders have an unrestrictively late common due date. The earliness and tardiness of the orders is minimized. Since the problem is NP-hard, we propose two hybridized genetic algorithms. Computational experiments on randomly generated problem instances are carried out that demonstrate that the genetic algorithms perform well.
具有共同到期日的单机多订单作业调度问题的遗传算法
本文讨论了一个多订单/作业(MOJ)调度问题。前开口统一吊舱(foup)在300mm晶圆厂中传输晶圆。多个订单可以分组在一个FOUP中,可以将其视为一个作业。假定了大量的加工环境。所有订单都有一个不受限制的延迟共同到期日。订单的提前和延迟被最小化。由于该问题是np困难的,我们提出了两种杂交遗传算法。在随机生成的问题实例上进行了计算实验,证明了遗传算法的良好性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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