Stochastic optimization model and solution algorithm for robust double-track train-timetabling problem

Muhammad Babar Khan, Xuesong Zhou

Research output: Contribution to journalArticle

44 Scopus citations

Abstract

By considering various stochastic disturbances unfolding in a real-time dispatching environment, this paper develops a stochastic optimization formulation for incorporating segment travel-time uncertainty and dispatching policies into a medium-term train-timetabling process that aims to minimize the total trip time in a published timetable and reduce the expected schedule delay. Based on a heuristic sequential solution framework, this study decomposes the robust timetabling problem into a series of subproblems that optimize the slack-time allocation for individual trains. A number of illustrative examples are provided to demonstrate the proposed model and solution algorithms using data collected from a BeijingShanghai high-speed rail corridor in China.

Original languageEnglish (US)
Article number5262983
Pages (from-to)81-89
Number of pages9
JournalIEEE Transactions on Intelligent Transportation Systems
Volume11
Issue number1
DOIs
StatePublished - Mar 1 2010
Externally publishedYes

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Keywords

  • Slack-time allocation
  • Stochastic optimization
  • Train scheduling
  • Train timetabling

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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