Joint optimization of train stop planning and timetabling with time-dependent passenger and freight demands in high-speed railway

IF 7.6 1区 工程技术 Q1 TRANSPORTATION SCIENCE & TECHNOLOGY Transportation Research Part C-Emerging Technologies Pub Date : 2025-02-14 DOI:10.1016/j.trc.2025.105025
Jianguo Qi , Yaru Zhou , Fanting Meng , Lixing Yang , Qin Luo , Chuntian Zhang
{"title":"Joint optimization of train stop planning and timetabling with time-dependent passenger and freight demands in high-speed railway","authors":"Jianguo Qi ,&nbsp;Yaru Zhou ,&nbsp;Fanting Meng ,&nbsp;Lixing Yang ,&nbsp;Qin Luo ,&nbsp;Chuntian Zhang","doi":"10.1016/j.trc.2025.105025","DOIUrl":null,"url":null,"abstract":"<div><div>To effectively utilize the remaining transportation capacity and increase the revenue of railway transport enterprises during periods of lower passenger demand, this study proposes a general framework for the joint optimization of train stop planning and timetabling problems based on a flexible train composition mode for passenger and freight co-transportation on high-speed railways. This framework aims to simultaneously provide different transport services for time-dependent passenger and freight demands. With the basic services being satisfied, a quadratic programming model is formulated to maximize the transportation revenue of railway companies by considering different operation costs of different types of train composition modes and minimizing the time deviations of passenger and freight compared with their desired service times. To effectively solve the proposed model, a heuristic approach combining the variable neighborhood search (VNS) and the commercial solver CPLEX is designed to search for high-quality solutions. Finally, the performance and effectiveness of the proposed approaches are verified using a small-scale example and a real case study of the Wuhan-Guangzhou high-speed railway.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"172 ","pages":"Article 105025"},"PeriodicalIF":7.6000,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part C-Emerging Technologies","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0968090X25000294","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TRANSPORTATION SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

To effectively utilize the remaining transportation capacity and increase the revenue of railway transport enterprises during periods of lower passenger demand, this study proposes a general framework for the joint optimization of train stop planning and timetabling problems based on a flexible train composition mode for passenger and freight co-transportation on high-speed railways. This framework aims to simultaneously provide different transport services for time-dependent passenger and freight demands. With the basic services being satisfied, a quadratic programming model is formulated to maximize the transportation revenue of railway companies by considering different operation costs of different types of train composition modes and minimizing the time deviations of passenger and freight compared with their desired service times. To effectively solve the proposed model, a heuristic approach combining the variable neighborhood search (VNS) and the commercial solver CPLEX is designed to search for high-quality solutions. Finally, the performance and effectiveness of the proposed approaches are verified using a small-scale example and a real case study of the Wuhan-Guangzhou high-speed railway.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
15.80
自引率
12.00%
发文量
332
审稿时长
64 days
期刊介绍: Transportation Research: Part C (TR_C) is dedicated to showcasing high-quality, scholarly research that delves into the development, applications, and implications of transportation systems and emerging technologies. Our focus lies not solely on individual technologies, but rather on their broader implications for the planning, design, operation, control, maintenance, and rehabilitation of transportation systems, services, and components. In essence, the intellectual core of the journal revolves around the transportation aspect rather than the technology itself. We actively encourage the integration of quantitative methods from diverse fields such as operations research, control systems, complex networks, computer science, and artificial intelligence. Join us in exploring the intersection of transportation systems and emerging technologies to drive innovation and progress in the field.
期刊最新文献
Editorial Board Deep imitative reinforcement learning with gradient conflict-free for decision-making in autonomous vehicles Efficient pedestrian and bicycle traffic flow estimation combining mobile-sourced data with route choice prediction Understanding the capacity of airport runway systems Real-time system optimal traffic routing under uncertainties — Can physics models boost reinforcement learning?
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1