设施选址中的分散起始解:平面 p 中值问题案例

IF 4.1 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Operations Research Pub Date : 2024-06-04 DOI:10.1016/j.cor.2024.106726
Zvi Drezner , Jack Brimberg , Anita Schöbel
{"title":"设施选址中的分散起始解:平面 p 中值问题案例","authors":"Zvi Drezner ,&nbsp;Jack Brimberg ,&nbsp;Anita Schöbel","doi":"10.1016/j.cor.2024.106726","DOIUrl":null,"url":null,"abstract":"<div><p>There are many planar multiple facilities location problems for which the optimal locations tend to be spread out. The most popular of these is the planar <span><math><mi>p</mi></math></span>-median problem. With this in mind, we propose several procedures to generate sparse configurations as starting solutions. The proposed procedures are easy to implement, and can be used as modules combined in different sequences within heuristics such as a recent trajectory-based procedure that we tested in this paper.</p><p>The procedures are tested experimentally on a set of 24 large problem instances with up to 10,000 demand points and 100 facilities. We are able to demonstrate that the sparse starting solutions generated by the new procedures lead to significant improvements of final <span><math><mi>p</mi></math></span>-median solutions.</p></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":null,"pages":null},"PeriodicalIF":4.1000,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0305054824001989/pdfft?md5=3e8bf98cdadb007c46b68379ed127281&pid=1-s2.0-S0305054824001989-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Dispersed starting solutions in facility location: The case of the planar p-median problem\",\"authors\":\"Zvi Drezner ,&nbsp;Jack Brimberg ,&nbsp;Anita Schöbel\",\"doi\":\"10.1016/j.cor.2024.106726\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>There are many planar multiple facilities location problems for which the optimal locations tend to be spread out. The most popular of these is the planar <span><math><mi>p</mi></math></span>-median problem. With this in mind, we propose several procedures to generate sparse configurations as starting solutions. The proposed procedures are easy to implement, and can be used as modules combined in different sequences within heuristics such as a recent trajectory-based procedure that we tested in this paper.</p><p>The procedures are tested experimentally on a set of 24 large problem instances with up to 10,000 demand points and 100 facilities. We are able to demonstrate that the sparse starting solutions generated by the new procedures lead to significant improvements of final <span><math><mi>p</mi></math></span>-median solutions.</p></div>\",\"PeriodicalId\":10542,\"journal\":{\"name\":\"Computers & Operations Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2024-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0305054824001989/pdfft?md5=3e8bf98cdadb007c46b68379ed127281&pid=1-s2.0-S0305054824001989-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Operations Research\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0305054824001989\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Operations Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0305054824001989","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

摘要

有许多平面多设施选址问题,其最佳选址往往比较分散。其中最常见的是平面 p 中值问题。有鉴于此,我们提出了几种生成稀疏配置作为起始解的程序。所提出的程序易于实现,并可作为启发式方法中不同序列的组合模块,例如我们在本文中测试的最新基于轨迹的程序。我们在一组 24 个大型问题实例上对这些程序进行了实验测试,这些实例包含多达 10,000 个需求点和 100 个设施。我们能够证明,新程序生成的稀疏起始解显著改善了最终的 p-median 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
Dispersed starting solutions in facility location: The case of the planar p-median problem

There are many planar multiple facilities location problems for which the optimal locations tend to be spread out. The most popular of these is the planar p-median problem. With this in mind, we propose several procedures to generate sparse configurations as starting solutions. The proposed procedures are easy to implement, and can be used as modules combined in different sequences within heuristics such as a recent trajectory-based procedure that we tested in this paper.

The procedures are tested experimentally on a set of 24 large problem instances with up to 10,000 demand points and 100 facilities. We are able to demonstrate that the sparse starting solutions generated by the new procedures lead to significant improvements of final p-median solutions.

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
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
Corporate risk stratification through an interpretable autoencoder-based model Re-direction in queueing networks with two customer types: The inter-departure analysis Multi objective optimization of human–robot collaboration: A case study in aerospace assembly line A deep reinforcement learning hyperheuristic for the covering tour problem with varying coverage Arc-flow formulation and branch-and-price-and-cut algorithm for the bin-packing problem with fragile objects
×
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