{"title":"全局求解用于 GPS 定位的分数平方最小二乘模型","authors":"Xiaoli Cen, Yong Xia","doi":"10.1007/s11075-024-01935-4","DOIUrl":null,"url":null,"abstract":"<p>This study presents a new branch and bound algorithm designed for the global optimization of the fractional squared least squares model for GPS localization. The algorithm incorporates a novel underestimation approach that provides theoretically superior lower bounds while requiring a comparable computational effort to the current approach. Numerical results demonstrate the substantial efficiency enhancements of the proposed algorithm over the existing algorithm.</p>","PeriodicalId":54709,"journal":{"name":"Numerical Algorithms","volume":"20 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Globally solving the fractional squared least squares model for GPS localization\",\"authors\":\"Xiaoli Cen, Yong Xia\",\"doi\":\"10.1007/s11075-024-01935-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This study presents a new branch and bound algorithm designed for the global optimization of the fractional squared least squares model for GPS localization. The algorithm incorporates a novel underestimation approach that provides theoretically superior lower bounds while requiring a comparable computational effort to the current approach. Numerical results demonstrate the substantial efficiency enhancements of the proposed algorithm over the existing algorithm.</p>\",\"PeriodicalId\":54709,\"journal\":{\"name\":\"Numerical Algorithms\",\"volume\":\"20 1\",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2024-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Numerical Algorithms\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1007/s11075-024-01935-4\",\"RegionNum\":3,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Numerical Algorithms","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s11075-024-01935-4","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
Globally solving the fractional squared least squares model for GPS localization
This study presents a new branch and bound algorithm designed for the global optimization of the fractional squared least squares model for GPS localization. The algorithm incorporates a novel underestimation approach that provides theoretically superior lower bounds while requiring a comparable computational effort to the current approach. Numerical results demonstrate the substantial efficiency enhancements of the proposed algorithm over the existing algorithm.
期刊介绍:
The journal Numerical Algorithms is devoted to numerical algorithms. It publishes original and review papers on all the aspects of numerical algorithms: new algorithms, theoretical results, implementation, numerical stability, complexity, parallel computing, subroutines, and applications. Papers on computer algebra related to obtaining numerical results will also be considered. It is intended to publish only high quality papers containing material not published elsewhere.