{"title":"Research on Optimization Problem of Routing about Parking Guidance Based on Improved Ant Colony Algorithm","authors":"Juan Li, Zi Li, Tao Sun, Meijuan Jia, Haitao Yu","doi":"10.1109/iccasit48058.2019.8973134","DOIUrl":null,"url":null,"abstract":"According to the layout characteristics of parking in the parking lot, the problem of converting the path choice of parking is raised to seek the optimal path and generate the optimal parking guiding line. This paper proposed the concept of node busy factor, and a mathematical model of the optimal path with constraints. The state transition rules of basic ant colony algorithm is improved as well as updating rules of pheromone. After that, the taboo strategy is introduced for further optimization. At last, the experimental results and Matlab simulation verify the effectiveness of the Algorithm.","PeriodicalId":289822,"journal":{"name":"2019 IEEE 1st International Conference on Civil Aviation Safety and Information Technology (ICCASIT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 1st International Conference on Civil Aviation Safety and Information Technology (ICCASIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iccasit48058.2019.8973134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
According to the layout characteristics of parking in the parking lot, the problem of converting the path choice of parking is raised to seek the optimal path and generate the optimal parking guiding line. This paper proposed the concept of node busy factor, and a mathematical model of the optimal path with constraints. The state transition rules of basic ant colony algorithm is improved as well as updating rules of pheromone. After that, the taboo strategy is introduced for further optimization. At last, the experimental results and Matlab simulation verify the effectiveness of the Algorithm.