{"title":"Passenger-Demands-Oriented Train Scheduling for a Bidirectional Urban Rail Transit Line","authors":"Jiawei Yuan","doi":"10.1109/ICECTT50890.2020.00119","DOIUrl":null,"url":null,"abstract":"The planning process of urban rail lines is a complex activity which is usually decomposed into several stages, traditionally network design, line planning, train scheduling, rolling stock scheduling, and crew scheduling. This paper focuses on the design and optimization of train scheduling for a urban rail transit line under the dynamic and oversaturated passenger demand. The objective is to minimize the total waiting time of passengers at platforms. In order to obtain high quality solutions, genetic algorithm is adopted to solve the proposed model. Finally, some numerical experiments based on Beijing ChangPing line are implemented to demonstrate the effectiveness of the proposed model and algorithm.","PeriodicalId":397407,"journal":{"name":"2020 5th International Conference on Electromechanical Control Technology and Transportation (ICECTT)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 5th International Conference on Electromechanical Control Technology and Transportation (ICECTT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECTT50890.2020.00119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The planning process of urban rail lines is a complex activity which is usually decomposed into several stages, traditionally network design, line planning, train scheduling, rolling stock scheduling, and crew scheduling. This paper focuses on the design and optimization of train scheduling for a urban rail transit line under the dynamic and oversaturated passenger demand. The objective is to minimize the total waiting time of passengers at platforms. In order to obtain high quality solutions, genetic algorithm is adopted to solve the proposed model. Finally, some numerical experiments based on Beijing ChangPing line are implemented to demonstrate the effectiveness of the proposed model and algorithm.