{"title":"设施选址中的分散起始解:平面 p 中值问题案例","authors":"Zvi Drezner , Jack Brimberg , 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 , Jack Brimberg , 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}
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 -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 -median solutions.
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.