考虑机器维修的混合多目标节能调度算法*

Junxia Xing, F. Qiao, Hong Lu
{"title":"考虑机器维修的混合多目标节能调度算法*","authors":"Junxia Xing, F. Qiao, Hong Lu","doi":"10.1109/COASE.2019.8843144","DOIUrl":null,"url":null,"abstract":"The aim of this paper is to address the energy-efficient scheduling problems in the hybrid flow shop problem (HFSP) with machine maintenance. For this aim, the mixed integer programming model (MIPM) considering energy consumption and machine maintenance is proposed firstly. Given the NP-hard nature of the model, a hybrid multi-objective algorithm (HMOA) combining an improved algorithm based on the Non-Dominated Sorting Genetic Algorithm (NSGA-II-imp) with a heuristic algorithm is developed to solve MIPM. The NSGA-II-imp designs a new elite remained strategy for the purpose of balancing two conflict objectives and a heuristic algorithm is mainly designed to add machine maintenance during production scheduling. Finally, the proposed algorithm is compared to GA, SA-GA, NSGA-II separately based on extensive numerical experiments. Results show the effectiveness of the algorithm in this paper.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"40 1","pages":"115-120"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"A Hybrid Multi-objective Algorithm for Energy-Efficient Scheduling Considering Machine Maintenance*\",\"authors\":\"Junxia Xing, F. Qiao, Hong Lu\",\"doi\":\"10.1109/COASE.2019.8843144\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this paper is to address the energy-efficient scheduling problems in the hybrid flow shop problem (HFSP) with machine maintenance. For this aim, the mixed integer programming model (MIPM) considering energy consumption and machine maintenance is proposed firstly. Given the NP-hard nature of the model, a hybrid multi-objective algorithm (HMOA) combining an improved algorithm based on the Non-Dominated Sorting Genetic Algorithm (NSGA-II-imp) with a heuristic algorithm is developed to solve MIPM. The NSGA-II-imp designs a new elite remained strategy for the purpose of balancing two conflict objectives and a heuristic algorithm is mainly designed to add machine maintenance during production scheduling. Finally, the proposed algorithm is compared to GA, SA-GA, NSGA-II separately based on extensive numerical experiments. Results show the effectiveness of the algorithm in this paper.\",\"PeriodicalId\":6695,\"journal\":{\"name\":\"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)\",\"volume\":\"40 1\",\"pages\":\"115-120\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COASE.2019.8843144\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COASE.2019.8843144","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

摘要

本文的目的是解决带有机器维修的混合流车间问题中的节能调度问题。为此,首先提出了考虑能耗和机器维护的混合整数规划模型(MIPM)。针对模型的NP-hard特性,提出了一种基于非支配排序遗传算法(NSGA-II-imp)的改进算法与启发式算法相结合的混合多目标算法(HMOA)来求解MIPM。NSGA-II-imp设计了一种新的精英保留策略,以平衡两个冲突目标,并设计了一种启发式算法,主要用于在生产调度中添加机器维护。最后,在大量数值实验的基础上,分别与GA、SA-GA、NSGA-II算法进行了比较。实验结果表明了本文算法的有效性。
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
A Hybrid Multi-objective Algorithm for Energy-Efficient Scheduling Considering Machine Maintenance*
The aim of this paper is to address the energy-efficient scheduling problems in the hybrid flow shop problem (HFSP) with machine maintenance. For this aim, the mixed integer programming model (MIPM) considering energy consumption and machine maintenance is proposed firstly. Given the NP-hard nature of the model, a hybrid multi-objective algorithm (HMOA) combining an improved algorithm based on the Non-Dominated Sorting Genetic Algorithm (NSGA-II-imp) with a heuristic algorithm is developed to solve MIPM. The NSGA-II-imp designs a new elite remained strategy for the purpose of balancing two conflict objectives and a heuristic algorithm is mainly designed to add machine maintenance during production scheduling. Finally, the proposed algorithm is compared to GA, SA-GA, NSGA-II separately based on extensive numerical experiments. Results show the effectiveness of the algorithm in this paper.
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
期刊最新文献
A proposed mapping method for aligning machine execution data to numerical control code optimizing outpatient Department Staffing Level using Multi-Fidelity Models Advanced Sensor and Target Development to Support Robot Accuracy Degradation Assessment Multi-Task Hierarchical Imitation Learning for Home Automation Deep Reinforcement Learning of Robotic Precision Insertion Skill Accelerated by Demonstrations
×
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