{"title":"An Ant Colony System algorithm for automatically schematizing transport network data sets","authors":"M. Ware, Nigel Richards","doi":"10.1109/CEC.2013.6557790","DOIUrl":null,"url":null,"abstract":"The work presented here investigates the usefulness of Ant Colony Optimisation to solving network schematization problems. This is a well-established problem domain and a number of solutions have appeared in the literature previously. In this paper an Ant Colony System (ACS) based algorithm is presented, together with experimental results and performance analysis. The aim is to provide an algorithm that produces better results and is more efficient (in terms of execution times) than previous solutions. Throughout the paper, ACS is tested and evaluated empirically - that is, experiments are performed and observed, these observations are recorded and subsequently analysed. In order to perform the experiments, a software implementation of the algorithm is constructed and then applied to test data sets. No attempt has been made here to perform a theoretical analysis of ACS. The results presented demonstrate that ACS can be used as an effective means of providing solutions to network schematization problems. In particular, ACS is shown to outperform a previous Simulated Annealing based solution.","PeriodicalId":211988,"journal":{"name":"2013 IEEE Congress on Evolutionary Computation","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Congress on Evolutionary Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEC.2013.6557790","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
The work presented here investigates the usefulness of Ant Colony Optimisation to solving network schematization problems. This is a well-established problem domain and a number of solutions have appeared in the literature previously. In this paper an Ant Colony System (ACS) based algorithm is presented, together with experimental results and performance analysis. The aim is to provide an algorithm that produces better results and is more efficient (in terms of execution times) than previous solutions. Throughout the paper, ACS is tested and evaluated empirically - that is, experiments are performed and observed, these observations are recorded and subsequently analysed. In order to perform the experiments, a software implementation of the algorithm is constructed and then applied to test data sets. No attempt has been made here to perform a theoretical analysis of ACS. The results presented demonstrate that ACS can be used as an effective means of providing solutions to network schematization problems. In particular, ACS is shown to outperform a previous Simulated Annealing based solution.