双机可重入流车间的批流调度

F. C. Çetinkaya, Mehmet Duman
{"title":"双机可重入流车间的批流调度","authors":"F. C. Çetinkaya, Mehmet Duman","doi":"10.31181/oresta111221142c","DOIUrl":null,"url":null,"abstract":"Lot streaming is splitting a job-lot of identical items into several sublots (portions of a lot) that can be moved to the next machines upon completion so that operations on successive machines can be overlapped; hence, the overall performance of a multi-stage manufacturing environment can be improved. In this study, we consider a scheduling problem with lot streaming in a two-machine re-entrant flow shop in which each job-lot is processed first on Machine 1, then goes to Machine 2 for its second operation before it returns to the primary machine (either Machine 1 or Machine 2) for the third operation. For the two cases of the primary machine, both single-job and multi-job cases are studied independently. Optimal and near-optimal solution procedures are developed. Our objective is to minimize the makespan, which is the maximum completion time of the sublots and job lots in the single-job and multi-job cases, respectively. We prove that the single-job problem is optimally solved in polynomial-time regardless of whether the third operation is performed on Machine 1 or Machine 2. The multi-job problem is also optimally solvable in polynomial time when the third operation is performed on Machine 2. However, we prove that the multi-job problem is NP-hard when the third operation is performed on Machine 1. A global lower bound on the makespan and a simple heuristic algorithm are developed. Our computational experiment results reveal that our proposed heuristic algorithm provides optimal or near-optimal solutions in a very short time.","PeriodicalId":36055,"journal":{"name":"Operational Research in Engineering Sciences: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Scheduling with lot streaming in a two-machine re-entrant flow shop\",\"authors\":\"F. C. Çetinkaya, Mehmet Duman\",\"doi\":\"10.31181/oresta111221142c\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Lot streaming is splitting a job-lot of identical items into several sublots (portions of a lot) that can be moved to the next machines upon completion so that operations on successive machines can be overlapped; hence, the overall performance of a multi-stage manufacturing environment can be improved. In this study, we consider a scheduling problem with lot streaming in a two-machine re-entrant flow shop in which each job-lot is processed first on Machine 1, then goes to Machine 2 for its second operation before it returns to the primary machine (either Machine 1 or Machine 2) for the third operation. For the two cases of the primary machine, both single-job and multi-job cases are studied independently. Optimal and near-optimal solution procedures are developed. Our objective is to minimize the makespan, which is the maximum completion time of the sublots and job lots in the single-job and multi-job cases, respectively. We prove that the single-job problem is optimally solved in polynomial-time regardless of whether the third operation is performed on Machine 1 or Machine 2. The multi-job problem is also optimally solvable in polynomial time when the third operation is performed on Machine 2. However, we prove that the multi-job problem is NP-hard when the third operation is performed on Machine 1. A global lower bound on the makespan and a simple heuristic algorithm are developed. Our computational experiment results reveal that our proposed heuristic algorithm provides optimal or near-optimal solutions in a very short time.\",\"PeriodicalId\":36055,\"journal\":{\"name\":\"Operational Research in Engineering Sciences: Theory and Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Operational Research in Engineering Sciences: Theory and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31181/oresta111221142c\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operational Research in Engineering Sciences: Theory and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31181/oresta111221142c","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 2

摘要

批次流是将一个相同项目的作业批次划分为几个子批次(批次的一部分),这些子批次可以在完成后移动到下一台机器,以便在连续机器上的操作可以重叠;因此,可以提高多阶段制造环境的整体性能。在这项研究中,我们考虑了一个在两台机器的可重入流车间中具有批次流的调度问题,在该车间中,每个作业批次首先在机器1上处理,然后进入机器2进行第二次操作,然后返回主机器(机器1或机器2)进行第三次操作。对于主机器的两种情况,单独研究了单作业和多作业情况。开发了最优和接近最优的求解程序。我们的目标是最大限度地缩短完工时间,即分别在单作业和多作业情况下子批次和作业批次的最大完工时间。我们证明了无论第三次运算是在机器1上还是在机器2上进行,单任务问题都能在多项式时间内最优求解。当在机器2上执行第三次操作时,多任务问题也可以在多项式时间内最优求解。然而,我们证明了当在机器1上执行第三次操作时,多任务问题是NP困难的。给出了完工时间的全局下界和一个简单的启发式算法。我们的计算实验结果表明,我们提出的启发式算法在很短的时间内提供了最优或接近最优的解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Scheduling with lot streaming in a two-machine re-entrant flow shop
Lot streaming is splitting a job-lot of identical items into several sublots (portions of a lot) that can be moved to the next machines upon completion so that operations on successive machines can be overlapped; hence, the overall performance of a multi-stage manufacturing environment can be improved. In this study, we consider a scheduling problem with lot streaming in a two-machine re-entrant flow shop in which each job-lot is processed first on Machine 1, then goes to Machine 2 for its second operation before it returns to the primary machine (either Machine 1 or Machine 2) for the third operation. For the two cases of the primary machine, both single-job and multi-job cases are studied independently. Optimal and near-optimal solution procedures are developed. Our objective is to minimize the makespan, which is the maximum completion time of the sublots and job lots in the single-job and multi-job cases, respectively. We prove that the single-job problem is optimally solved in polynomial-time regardless of whether the third operation is performed on Machine 1 or Machine 2. The multi-job problem is also optimally solvable in polynomial time when the third operation is performed on Machine 2. However, we prove that the multi-job problem is NP-hard when the third operation is performed on Machine 1. A global lower bound on the makespan and a simple heuristic algorithm are developed. Our computational experiment results reveal that our proposed heuristic algorithm provides optimal or near-optimal solutions in a very short time.
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
CiteScore
7.90
自引率
0.00%
发文量
25
审稿时长
15 weeks
期刊最新文献
Non-Pharmaceutical Intervention Strategies to Respond to the COVID-19 Pandemic: Preference Ranking Method Ranking the Recreational Leadership Factors in the Behavioral Dimension and Selection of the Most Ideal Organizational Citizenship Model A Two-Stage Integrated Model for Supplier Selection and Order Allocation: An Application in Dairy Industry Simulation of Job Sequencing for Stochastic Scheduling with a Genetic Algorithm Optimal Load Scheduling of Home Appliances Considering Operation Conditions
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1