{"title":"Operation extension strategy on last train timetables in urban rail transit network: A Pareto optimality-based approach","authors":"","doi":"10.1007/s11116-024-10483-8","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>Under the increasingly prosperous nighttime economy, it is necessary to develop an operation extension strategy to optimize last train connections to improve urban rail transit service levels. A novel MILP model is proposed that aims to optimize operation extension strategy for last train timetables. Pareto's principle is adopted to deal with two goals: maximizing the social benefits and minimizing the operation costs. Given the large scale of urban rail transit (URT) networks, a hybrid "Pareto + Cplex" solution algorithm is devised. The algorithm decomposes the integrated optimization problem into two subproblems: adjusted line identification, and last train timetable optimization. To verify its performance, the proposed methodology was applied to the Beijing subway network. The ratio of successfully transferred passengers for the last trains across the thirteen lines increased from 46.33% to a maximum of 63.91%. Interestingly, the results show that the lines adjusted to achieve the optimized results went against common sense; the highest successful transfer rate of the last train in the network would be reached before all lines were considered as adjusted objects, and the operator could focus on a few crucial lines to significantly improve the last train connection effect. Consequently, the proposed optimization scheme assists operators in making informed decisions regarding the connections of last train timetables, leading to more scientific and refined management of URT networks.</p>","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"46 1","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s11116-024-10483-8","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
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Abstract
Under the increasingly prosperous nighttime economy, it is necessary to develop an operation extension strategy to optimize last train connections to improve urban rail transit service levels. A novel MILP model is proposed that aims to optimize operation extension strategy for last train timetables. Pareto's principle is adopted to deal with two goals: maximizing the social benefits and minimizing the operation costs. Given the large scale of urban rail transit (URT) networks, a hybrid "Pareto + Cplex" solution algorithm is devised. The algorithm decomposes the integrated optimization problem into two subproblems: adjusted line identification, and last train timetable optimization. To verify its performance, the proposed methodology was applied to the Beijing subway network. The ratio of successfully transferred passengers for the last trains across the thirteen lines increased from 46.33% to a maximum of 63.91%. Interestingly, the results show that the lines adjusted to achieve the optimized results went against common sense; the highest successful transfer rate of the last train in the network would be reached before all lines were considered as adjusted objects, and the operator could focus on a few crucial lines to significantly improve the last train connection effect. Consequently, the proposed optimization scheme assists operators in making informed decisions regarding the connections of last train timetables, leading to more scientific and refined management of URT networks.
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In our first issue, published in 1972, we explained that this Journal is intended to promote the free and vigorous exchange of ideas and experience among the worldwide community actively concerned with transportation policy, planning and practice. That continues to be our mission, with a clear focus on topics concerned with research and practice in transportation policy and planning, around the world.
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