{"title":"A New Column-Row Method for Traveling Salesman Problem: The Dhouib-Matrix-TSP1","authors":"S. Dhouib","doi":"10.14445/23497157/ijres-v8i1p102","DOIUrl":null,"url":null,"abstract":"In this paper, a new column-row method named Dhouib-Matrix-TSP1 is designed to solve in polynomial time the Traveling Salesman Problem (TSP). At first, the distance matrix is defined, and then four steps are launched: 1) Selecting the starting position 2) Choosing Rows 3) Discarding by column 3) Transforming route to a tour. Some numerical examples are presented to illustrate the effectiveness of the proposed method. It can be concluded that the Dhouib-Matrix-TSP1 method consumes a small number of iterations (just n iterations, where n represents the number of cities) to solve the TSP, and its result is the closest to the optimum solution.","PeriodicalId":14292,"journal":{"name":"International Journal of Recent Engineering Science","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Recent Engineering Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14445/23497157/ijres-v8i1p102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
In this paper, a new column-row method named Dhouib-Matrix-TSP1 is designed to solve in polynomial time the Traveling Salesman Problem (TSP). At first, the distance matrix is defined, and then four steps are launched: 1) Selecting the starting position 2) Choosing Rows 3) Discarding by column 3) Transforming route to a tour. Some numerical examples are presented to illustrate the effectiveness of the proposed method. It can be concluded that the Dhouib-Matrix-TSP1 method consumes a small number of iterations (just n iterations, where n represents the number of cities) to solve the TSP, and its result is the closest to the optimum solution.