{"title":"Using the Ant Colony Optimization algorithm for the Capacitated Vehicle Routing Problem","authors":"P. Stodola, J. Mazal, M. Podhorec, O. Litvaj","doi":"10.1109/MECHATRONIKA.2014.7018311","DOIUrl":null,"url":null,"abstract":"This paper deals with the application of the Ant Colony Optimization (ACO) algorithm to solve the Capacitated Vehicle Routing Problem (CVRP). The first part presents the basic approach and concept which has been inspired by nature. Next, the basic features and parameters of the algorithm are discussed. Then, a number of experiments are introduced which served to verify the algorithm. We chose Christofides, Mingozzi and Toth's CVRP instances as benchmark problems. The results we obtained are compared with other state-of-the-art algorithms. Next, the improvement of the algorithm is presented. The last part of the paper presents the application of the problem in practice; the primary objective is to plan the distribution of supplies and logistics in the real environment. Finally, the paper summarizes some perspectives of our future work.","PeriodicalId":430829,"journal":{"name":"Proceedings of the 16th International Conference on Mechatronics - Mechatronika 2014","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 16th International Conference on Mechatronics - Mechatronika 2014","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MECHATRONIKA.2014.7018311","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
This paper deals with the application of the Ant Colony Optimization (ACO) algorithm to solve the Capacitated Vehicle Routing Problem (CVRP). The first part presents the basic approach and concept which has been inspired by nature. Next, the basic features and parameters of the algorithm are discussed. Then, a number of experiments are introduced which served to verify the algorithm. We chose Christofides, Mingozzi and Toth's CVRP instances as benchmark problems. The results we obtained are compared with other state-of-the-art algorithms. Next, the improvement of the algorithm is presented. The last part of the paper presents the application of the problem in practice; the primary objective is to plan the distribution of supplies and logistics in the real environment. Finally, the paper summarizes some perspectives of our future work.