Piotr Jarecki, Pawel Kopec, I. Pozniak-Koszalka, L. Koszalka, A. Kasprzak, G. Chmaj
{"title":"Comparison of Algorithms for Finding Best Route in an Area with Obstacles","authors":"Piotr Jarecki, Pawel Kopec, I. Pozniak-Koszalka, L. Koszalka, A. Kasprzak, G. Chmaj","doi":"10.1109/ICSEng.2017.51","DOIUrl":null,"url":null,"abstract":"In this paper, the problem of finding the route between two distinguished points in an area with obstacles is considered. The problem consists in minimizing the introduced cost function which is taken into account the necessity of crossing some intermediate points. The created and implemented algorithm to solving this problem is based on ant colony optimization. This algorithm is compared with the other implemented heuristic algorithms which had been designed according to genetic algorithm idea, and simulated annealing. The comparative analysis of algorithms' properties is made on the basis of the results of simulations made with the designed and implemented experimentation system. The obtained results of experiments confirmed that the proposed algorithm seems to be very promising.","PeriodicalId":202005,"journal":{"name":"2017 25th International Conference on Systems Engineering (ICSEng)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 25th International Conference on Systems Engineering (ICSEng)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSEng.2017.51","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper, the problem of finding the route between two distinguished points in an area with obstacles is considered. The problem consists in minimizing the introduced cost function which is taken into account the necessity of crossing some intermediate points. The created and implemented algorithm to solving this problem is based on ant colony optimization. This algorithm is compared with the other implemented heuristic algorithms which had been designed according to genetic algorithm idea, and simulated annealing. The comparative analysis of algorithms' properties is made on the basis of the results of simulations made with the designed and implemented experimentation system. The obtained results of experiments confirmed that the proposed algorithm seems to be very promising.