A Two-Objective Timetable Optimization Model in Subway Systems

Xin Yang, Bin Ning, Xiang Li, Tao Tang

Research output: Contribution to journalArticlepeer-review

161 Citations (SciVal)

Abstract

The train timetable optimization problem in subway systems is to determine arrival and departure times for trains at stations so that the resources can be effectively utilized and the trains can be efficiently operated. Because the energy saving and the service quality are paid more attention, this paper proposes a timetable optimization model to increase the utilization of regenerative energy and, simultaneously, to shorten the passenger waiting time. First, we formulate a two-objective integer programming model with headway time and dwell time control. Second, we design a genetic algorithm with binary encoding to find the optimal solution. Finally, we conduct numerical examples based on the operation data from the Beijing Yizhuang subway line of China. The results illustrate that the proposed model can save energy by 8.86% and reduce passenger waiting time by 3.22% in comparison with the current timetable.
Original languageEnglish
Pages (from-to)1913-1921
Number of pages9
JournalIEEE Transactions on Intelligent Transportation Systems
Volume15
Issue number5
Early online date19 Feb 2014
DOIs
Publication statusPublished - 31 Oct 2014
Externally publishedYes

Keywords

  • Genetic algorithm (GA)
  • passenger waiting time
  • regenerative energy
  • subway systems
  • timetable optimization

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