Modeling and solving the multi-objective energy-efficient production planning and scheduling with imperfect maintenance activities

IF 1.8 Q3 ENGINEERING, INDUSTRIAL
I. Rastgar, J. Rezaeian, I. Mahdavi, P. Fattahi
{"title":"Modeling and solving the multi-objective energy-efficient production planning and scheduling with imperfect maintenance activities","authors":"I. Rastgar, J. Rezaeian, I. Mahdavi, P. Fattahi","doi":"10.1108/jqme-10-2022-0068","DOIUrl":null,"url":null,"abstract":"PurposeThe purpose of this study is to propose a new mathematical model that integrates strategic decision-making with tactical-operational decision-making in order to optimize production and scheduling decisions.Design/methodology/approachThis study presents a multi-objective optimization framework to make production planning, scheduling and maintenance decisions. An epsilon-constraint method is used to solve small instances of the model, while new hybrid optimization algorithms, including multi-objective particle swarm optimization (MOPSO), non-dominated sorting genetic algorithm, multi-objective harmony search and improved multi-objective harmony search (IMOHS) are developed to address the high complexity of large-scale problems.FindingsThe computational results demonstrate that the metaheuristic algorithms are effective in obtaining economic solutions within a reasonable computational time. In particular, the results show that the IMOHS algorithm is able to provide optimal Pareto solutions for the proposed model compared to the other three algorithms.Originality/valueThis study presents a new mathematical model that simultaneously determines green production planning and scheduling decisions by minimizing the sum of the total cost, makespan, lateness and energy consumption criteria. Integrating production and scheduling of a shop floor is critical for achieving optimal operational performance in production planning. To the best of the authors' knowledge, the integration of production planning and maintenance has not been adequately addressed.","PeriodicalId":16938,"journal":{"name":"Journal of Quality in Maintenance Engineering","volume":"90 7","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Quality in Maintenance Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/jqme-10-2022-0068","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0

Abstract

PurposeThe purpose of this study is to propose a new mathematical model that integrates strategic decision-making with tactical-operational decision-making in order to optimize production and scheduling decisions.Design/methodology/approachThis study presents a multi-objective optimization framework to make production planning, scheduling and maintenance decisions. An epsilon-constraint method is used to solve small instances of the model, while new hybrid optimization algorithms, including multi-objective particle swarm optimization (MOPSO), non-dominated sorting genetic algorithm, multi-objective harmony search and improved multi-objective harmony search (IMOHS) are developed to address the high complexity of large-scale problems.FindingsThe computational results demonstrate that the metaheuristic algorithms are effective in obtaining economic solutions within a reasonable computational time. In particular, the results show that the IMOHS algorithm is able to provide optimal Pareto solutions for the proposed model compared to the other three algorithms.Originality/valueThis study presents a new mathematical model that simultaneously determines green production planning and scheduling decisions by minimizing the sum of the total cost, makespan, lateness and energy consumption criteria. Integrating production and scheduling of a shop floor is critical for achieving optimal operational performance in production planning. To the best of the authors' knowledge, the integration of production planning and maintenance has not been adequately addressed.
不完美维护活动下的多目标节能生产规划与调度建模与求解
本研究旨在提出一种新的数学模型,将战略决策与战术运营决策相结合,以优化生产和调度决策。使用ε约束方法解决模型的小实例,同时开发了新的混合优化算法,包括多目标粒子群优化(MOPSO)、非支配排序遗传算法、多目标和谐搜索和改进的多目标和谐搜索(IMOHS),以解决大规模问题的高复杂性。特别是,结果表明,与其他三种算法相比,IMOHS 算法能够为所提出的模型提供最优帕累托解决方案。原创性/价值本研究提出了一种新的数学模型,通过最小化总成本、生产周期、延迟和能耗标准的总和,同时确定绿色生产计划和排程决策。整合车间的生产和调度对于实现生产计划的最佳运营绩效至关重要。据作者所知,生产计划与维护的整合尚未得到充分解决。
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
Journal of Quality in Maintenance Engineering
Journal of Quality in Maintenance Engineering Engineering-Safety, Risk, Reliability and Quality
CiteScore
4.00
自引率
13.30%
发文量
24
期刊介绍: This exciting journal looks at maintenance engineering from a positive standpoint, and clarifies its recently elevatedstatus as a highly technical, scientific, and complex field. Typical areas examined include: ■Budget and control ■Equipment management ■Maintenance information systems ■Process capability and maintenance ■Process monitoring techniques ■Reliability-based maintenance ■Replacement and life cycle costs ■TQM and maintenance
×
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