Article(id=1318999743582290356, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1318999703161782439, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1672-6073.2025.04.017, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1730822400000, receivedDateStr=2024-11-06, revisedDate=1747756800000, revisedDateStr=2025-05-21, acceptedDate=null, acceptedDateStr=null, onlineDate=1792403644699, onlineDateStr=2026-10-19, pubDate=1754755200000, pubDateStr=2025-08-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792403644699, onlineIssueDateStr=2026-10-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792403644699, creator=13701087609, updateTime=1792403644699, updator=13701087609, issue=Issue{id=1318999703161782439, tenantId=1146029695717560320, journalId=1146123302524792850, year='2025', volume='38', issue='4', pageStart='1', pageEnd='159', issueExtLink='null', onlineDate='null', pubDate='1754755200000', pubDateStr='2025-08-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792403635062, creator='13701087609', updateTime=1792733364265, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1320382687735558277, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1318999703161782439, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1320382687735558278, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1318999703161782439, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=125, endPage=133, ext={EN=ArticleExt(id=1318999743775228341, articleId=1318999743582290356, tenantId=1146029695717560320, journalId=1146123302524792850, language=EN, title=Optimization of Urban Rail Transit Timetable Based on Long-Short Routes and Passenger Flow Control, columnId=1153381654128218984, journalTitle=Urban Rapid Rail Transit, columnName=Operation Management, runingTitle=null, highlight=null, articleAbstract=

In major metropolitan areas, the severe congestion during peak hours at urban rail transit stations necessitates comprehensive research on train timetable, particularly focusing on the implementation of short-turn and full-length routing strategies coupled with passenger flow control measures. This study takes the morning peak period of urban rail transit lines as its research subject, establishing an optimization model for train timetables by considering passenger travel costs and enterprise operational expenses as the objective functions, while incorporating constraints such as train departure intervals, vehicle capacity, passenger flow control, and routing strategies. Utilizing a linear weighting method to balance both passenger and operational costs, the research develops a genetic algorithm for model solution, with Hangzhou Metro Line 4 serving as a case study. The findings demonstrate that optimized train schedules effectively reduce passenger travel costs, while the implementation of short-turn and full-length routing strategies contributes to lowering operational expenses for enterprises. Furthermore, the integration of passenger flow control measures significantly alleviates station congestion levels. This research on timetable optimization, based on routing strategies and passenger flow control, provides valuable insights for rail transit enterprises in formulating effective peak-hour dispatching strategies.

, authors=Yingwen JI, Lanfen LIU, Jiaying YAO, Hongyun ZHAO, authorsList=Yingwen JI, Lanfen LIU, Jiaying YAO, Hongyun ZHAO, authorCompany=null, correspAuthors=Lanfen LIU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1318999743993332150, articleId=1318999743582290356, tenantId=1146029695717560320, journalId=1146123302524792850, language=CN, title=基于大小交路与客流控制的城轨列车时刻表优化研究, columnId=1153381654287602537, journalTitle=都市快轨交通, columnName=运营管理, runingTitle=null, highlight=null, articleAbstract=

部分大城市轨道交通车站高峰期拥堵严重，亟需从大小交路方案与客流控制策略等方面对列车时刻表进行研究。以早高峰时期城市轨道交通线路为研究对象，将乘客出行成本、企业运营成本作为目标函数，考虑发车间隔、列车容量、客流控制、大小交路方案等约束条件建立列车时刻表优化模型。采用线性加权法兼顾乘客出行及企业运营成本，并设计模型求解的遗传算法，以杭州地铁4号线为例进行验证，结果表明：对列车时刻表进行优化可以降低乘客出行的成本，同时大小交路的方案有助于企业降低运营成本；同步考虑客流控制，可进一步缓解站内拥挤程度。基于大小交路及客流控制研究时刻表优化问题，可对轨道交通企业高峰期调度策略的制定提供支持。

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