{"title":"基于凸分析的费马-托里拆利问题及Weiszfeld算法","authors":"B. Mordukhovich, N. M. Nam","doi":"10.23952/jano.1.2019.3.02","DOIUrl":null,"url":null,"abstract":"In the early 17th century, Pierre de Fermat proposed the following problem: given three points in the plane, find a point such that the sum of its Euclidean distances to the three given points is minimal. This problem was solved by Evangelista Torricelli and was named the {\\em Fermat-Torricelli problem}. A more general version of the Fermat-Torricelli problem asks for a point that minimizes the sum of the distances to a finite number of given points in $\\Bbb R^n$. This is one of the main problems in location science. In this paper we revisit the Fermat-Torricelli problem from both theoretical and numerical viewpoints using some ingredients of convex analysis and optimization.","PeriodicalId":205734,"journal":{"name":"Journal of Applied and Numerical Optimization","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"The Fermat-Torricelli problem and Weiszfeld’s algorithm in the light of convex analysis\",\"authors\":\"B. Mordukhovich, N. M. Nam\",\"doi\":\"10.23952/jano.1.2019.3.02\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the early 17th century, Pierre de Fermat proposed the following problem: given three points in the plane, find a point such that the sum of its Euclidean distances to the three given points is minimal. This problem was solved by Evangelista Torricelli and was named the {\\\\em Fermat-Torricelli problem}. A more general version of the Fermat-Torricelli problem asks for a point that minimizes the sum of the distances to a finite number of given points in $\\\\Bbb R^n$. This is one of the main problems in location science. In this paper we revisit the Fermat-Torricelli problem from both theoretical and numerical viewpoints using some ingredients of convex analysis and optimization.\",\"PeriodicalId\":205734,\"journal\":{\"name\":\"Journal of Applied and Numerical Optimization\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-02-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Applied and Numerical Optimization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23952/jano.1.2019.3.02\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied and Numerical Optimization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23952/jano.1.2019.3.02","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
摘要
17世纪初,皮埃尔·德·费马(Pierre de Fermat)提出了这样一个问题:给定平面上的三个点,找出一个点与这三个点的欧氏距离之和最小。这个问题被埃万杰里斯塔·托里拆利解决了,并被命名为费马-托里拆利问题。费马-托里拆利问题的一个更一般的版本要求在$\Bbb R^n$中找到一个点,使到有限个给定点的距离和最小。这是定位科学的主要问题之一。本文利用凸分析和最优化的一些成分,从理论和数值两方面重新讨论了费马-托里拆利问题。
The Fermat-Torricelli problem and Weiszfeld’s algorithm in the light of convex analysis
In the early 17th century, Pierre de Fermat proposed the following problem: given three points in the plane, find a point such that the sum of its Euclidean distances to the three given points is minimal. This problem was solved by Evangelista Torricelli and was named the {\em Fermat-Torricelli problem}. A more general version of the Fermat-Torricelli problem asks for a point that minimizes the sum of the distances to a finite number of given points in $\Bbb R^n$. This is one of the main problems in location science. In this paper we revisit the Fermat-Torricelli problem from both theoretical and numerical viewpoints using some ingredients of convex analysis and optimization.