D. Peña, Andrei Tchernykh, Sergio Nesmachnow, R. Massobrio, A. Drozdov, S. Garichev
{"title":"Multiobjective Vehicle Type and Size Scheduling Problem in Urban Public Transport Using MOCell","authors":"D. Peña, Andrei Tchernykh, Sergio Nesmachnow, R. Massobrio, A. Drozdov, S. Garichev","doi":"10.1109/ENT.2016.032","DOIUrl":null,"url":null,"abstract":"We study the problem of vehicle scheduling in urban public transport systems taking into account the vehicle-type and size (VTSP). It is modeled as a multiobjective combinatorial optimization problem. A heuristic based on MOCell (Multi-Objective Cellular evolutionary algorithm) is proposed to solve the problem. A set of non-dominated solutions represents different assignments of vehicles to specific routes. The conflicting objectives of provider and users (passenger) are to minimize the total operating cost, and maximize the quality of service, taking into account restrictions of government agencies in context of smart cities to improve the Intelligent Transport Systems (ITS).","PeriodicalId":356690,"journal":{"name":"2016 International Conference on Engineering and Telecommunication (EnT)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Engineering and Telecommunication (EnT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ENT.2016.032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
We study the problem of vehicle scheduling in urban public transport systems taking into account the vehicle-type and size (VTSP). It is modeled as a multiobjective combinatorial optimization problem. A heuristic based on MOCell (Multi-Objective Cellular evolutionary algorithm) is proposed to solve the problem. A set of non-dominated solutions represents different assignments of vehicles to specific routes. The conflicting objectives of provider and users (passenger) are to minimize the total operating cost, and maximize the quality of service, taking into account restrictions of government agencies in context of smart cities to improve the Intelligent Transport Systems (ITS).