{"title":"A novel ant colony system for solving the one-commodity traveling salesman problem with selective pickup and delivery","authors":"Lian-Ming Mou, X. Dai","doi":"10.1109/ICNC.2012.6234622","DOIUrl":null,"url":null,"abstract":"The one-commodity traveling salesman problem with selective pickup and delivery (1-TSP-SELPD) is a generalization of the one-commodity pickup-and-delivery traveling salesman problem (1-PDTSP) and has many interesting applications. The 1-TSP-SELPD is known to be an NP-hard. In this paper, to solve effectively the 1-TSP-SELPD, we extend the ant colony system method from TSP to 1-TSP-SELPD. Meanwhile, to improve the quality of solution, the constrained local searching and neighborhood searching technique are introduced into this method to accelerate the convergence according to the characteristic of the 1-TSP-SELPD, and a novel mutation technique is also introduced into this method to avoid falling into local minima. Experimental results gathered from extensive simulations confirm that our proposed method is significantly superior to the state-of-the-art methods.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"23 1","pages":"1096-1101"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2012.6234622","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
The one-commodity traveling salesman problem with selective pickup and delivery (1-TSP-SELPD) is a generalization of the one-commodity pickup-and-delivery traveling salesman problem (1-PDTSP) and has many interesting applications. The 1-TSP-SELPD is known to be an NP-hard. In this paper, to solve effectively the 1-TSP-SELPD, we extend the ant colony system method from TSP to 1-TSP-SELPD. Meanwhile, to improve the quality of solution, the constrained local searching and neighborhood searching technique are introduced into this method to accelerate the convergence according to the characteristic of the 1-TSP-SELPD, and a novel mutation technique is also introduced into this method to avoid falling into local minima. Experimental results gathered from extensive simulations confirm that our proposed method is significantly superior to the state-of-the-art methods.