Scheduling AMSs with generalized Petri nets and highly informed heuristic search

IF 4.1 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Operations Research Pub Date : 2024-11-18 DOI:10.1016/j.cor.2024.106912
FengLian Yuan , Bo Huang , JianYong Lv , MeiJi Cui
{"title":"Scheduling AMSs with generalized Petri nets and highly informed heuristic search","authors":"FengLian Yuan ,&nbsp;Bo Huang ,&nbsp;JianYong Lv ,&nbsp;MeiJi Cui","doi":"10.1016/j.cor.2024.106912","DOIUrl":null,"url":null,"abstract":"<div><div>The design of the heuristic function in a Petri-net(PN)-based A<span><math><msup><mrow></mrow><mrow><mo>∗</mo></mrow></msup></math></span> search significantly impacts search efficiency and schedule quality for automated manufacturing systems (AMSs). In Luo et al. (2015), two admissible heuristic functions were formulated for an A<span><math><msup><mrow></mrow><mrow><mo>∗</mo></mrow></msup></math></span> search based on place-timed PNs to schedule AMSs. To broaden its application scenarios and enhance search efficiency, this paper proposes a new heuristic function whose calculations take account of multiple resource acquisitions, weighted arcs, redundant resource units, and outdated resources, which are commonly encountered in practical AMSs but usually not considered. The proposed one can deal with generalized PNs, offering broader application scenarios than ordinary PNs. In addition, it is proven to be admissible and more informed than its counterparts, ensuring that the obtained schedules are optimal and making the timed PN-based A<span><math><msup><mrow></mrow><mrow><mo>∗</mo></mrow></msup></math></span> search more efficient. To validate the efficacy and efficiency of the proposed method, several benchmark systems are tested.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"175 ","pages":"Article 106912"},"PeriodicalIF":4.1000,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Operations Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0305054824003848","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

The design of the heuristic function in a Petri-net(PN)-based A search significantly impacts search efficiency and schedule quality for automated manufacturing systems (AMSs). In Luo et al. (2015), two admissible heuristic functions were formulated for an A search based on place-timed PNs to schedule AMSs. To broaden its application scenarios and enhance search efficiency, this paper proposes a new heuristic function whose calculations take account of multiple resource acquisitions, weighted arcs, redundant resource units, and outdated resources, which are commonly encountered in practical AMSs but usually not considered. The proposed one can deal with generalized PNs, offering broader application scenarios than ordinary PNs. In addition, it is proven to be admissible and more informed than its counterparts, ensuring that the obtained schedules are optimal and making the timed PN-based A search more efficient. To validate the efficacy and efficiency of the proposed method, several benchmark systems are tested.
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
利用广义 Petri 网和高度知情的启发式搜索安排 AMS
在基于 Petri 网(PN)的 A∗ 搜索中,启发式函数的设计对自动制造系统(AMS)的搜索效率和排程质量有很大影响。在 Luo 等人(2015 年)的研究中,为基于位置定时 PN 的 A∗ 搜索制定了两个可接受的启发式函数,以调度 AMS。为了拓宽其应用场景并提高搜索效率,本文提出了一种新的启发式函数,其计算考虑了实际 AMS 中经常遇到但通常不考虑的多资源获取、加权弧、冗余资源单元和过时资源。所提出的计算方法可以处理广义 PN,提供比普通 PN 更广泛的应用场景。此外,它还被证明是可接受的,并且比同类算法更有信息量,从而确保获得的计划是最优的,并使基于定时 PN 的 A∗ 搜索更有效率。为了验证所提方法的功效和效率,对几个基准系统进行了测试。
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 去求助
来源期刊
Computers & Operations Research
Computers & Operations Research 工程技术-工程:工业
CiteScore
8.60
自引率
8.70%
发文量
292
审稿时长
8.5 months
期刊介绍: Operations research and computers meet in a large number of scientific fields, many of which are of vital current concern to our troubled society. These include, among others, ecology, transportation, safety, reliability, urban planning, economics, inventory control, investment strategy and logistics (including reverse logistics). Computers & Operations Research provides an international forum for the application of computers and operations research techniques to problems in these and related fields.
期刊最新文献
Understand your decision rather than your model prescription: Towards explainable deep learning approaches for commodity procurement Airline recovery problem under disruptions: A review A decomposition scheme for Wasserstein distributionally robust emergency relief network design under demand uncertainty and social donations Scheduling AMSs with generalized Petri nets and highly informed heuristic search Efficient arc-flow formulations for makespan minimisation on parallel machines with a common server
×
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