{"title":"完全顶点p中心问题","authors":"F.Antonio Medrano","doi":"10.1007/s13675-020-00131-y","DOIUrl":null,"url":null,"abstract":"<div><p>The vertex <em>p</em>-center problem consists of locating <em>p</em> facilities among a set of <em>M</em> potential sites such that the maximum distance from any demand to its closest located facility is minimized. The complete vertex <em>p</em>-center problem solves the <em>p</em>-center problem for all <em>p</em> from 1 to the total number of sites, resulting in a multi-objective trade-off curve between the number of facilities and the service distance required to achieve full coverage. This trade-off provides a reference to planners and decision makers, enabling them to easily visualize the consequences of choosing different coverage design criteria for the given spatial configuration of the problem. We present two fast algorithms for solving the complete <em>p</em>-center problem: one using the classical formulation but trimming variables while still maintaining optimality and the other converting the problem to a location set covering problem and solving for all distances in the distance matrix. We also discuss scenarios where it makes sense to solve the problem via brute-force enumeration. All methods result in significant speedups, with the set covering method reducing computation times by many orders of magnitude.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"8 3","pages":"Pages 327-343"},"PeriodicalIF":2.6000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s13675-020-00131-y","citationCount":"1","resultStr":"{\"title\":\"The complete vertex p-center problem\",\"authors\":\"F.Antonio Medrano\",\"doi\":\"10.1007/s13675-020-00131-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The vertex <em>p</em>-center problem consists of locating <em>p</em> facilities among a set of <em>M</em> potential sites such that the maximum distance from any demand to its closest located facility is minimized. The complete vertex <em>p</em>-center problem solves the <em>p</em>-center problem for all <em>p</em> from 1 to the total number of sites, resulting in a multi-objective trade-off curve between the number of facilities and the service distance required to achieve full coverage. This trade-off provides a reference to planners and decision makers, enabling them to easily visualize the consequences of choosing different coverage design criteria for the given spatial configuration of the problem. We present two fast algorithms for solving the complete <em>p</em>-center problem: one using the classical formulation but trimming variables while still maintaining optimality and the other converting the problem to a location set covering problem and solving for all distances in the distance matrix. We also discuss scenarios where it makes sense to solve the problem via brute-force enumeration. All methods result in significant speedups, with the set covering method reducing computation times by many orders of magnitude.</p></div>\",\"PeriodicalId\":51880,\"journal\":{\"name\":\"EURO Journal on Computational Optimization\",\"volume\":\"8 3\",\"pages\":\"Pages 327-343\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2020-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1007/s13675-020-00131-y\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EURO Journal on Computational Optimization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2192440621001337\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EURO Journal on Computational Optimization","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2192440621001337","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
The vertex p-center problem consists of locating p facilities among a set of M potential sites such that the maximum distance from any demand to its closest located facility is minimized. The complete vertex p-center problem solves the p-center problem for all p from 1 to the total number of sites, resulting in a multi-objective trade-off curve between the number of facilities and the service distance required to achieve full coverage. This trade-off provides a reference to planners and decision makers, enabling them to easily visualize the consequences of choosing different coverage design criteria for the given spatial configuration of the problem. We present two fast algorithms for solving the complete p-center problem: one using the classical formulation but trimming variables while still maintaining optimality and the other converting the problem to a location set covering problem and solving for all distances in the distance matrix. We also discuss scenarios where it makes sense to solve the problem via brute-force enumeration. All methods result in significant speedups, with the set covering method reducing computation times by many orders of magnitude.
期刊介绍:
The aim of this journal is to contribute to the many areas in which Operations Research and Computer Science are tightly connected with each other. More precisely, the common element in all contributions to this journal is the use of computers for the solution of optimization problems. Both methodological contributions and innovative applications are considered, but validation through convincing computational experiments is desirable. The journal publishes three types of articles (i) research articles, (ii) tutorials, and (iii) surveys. A research article presents original methodological contributions. A tutorial provides an introduction to an advanced topic designed to ease the use of the relevant methodology. A survey provides a wide overview of a given subject by summarizing and organizing research results.