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Timetable Synchronization Optimization for Urban Rail Transit Network

Vosoughinia, Sajjad | 2022

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55390 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Shafahi, Yousef
  7. Abstract:
  8. Scheduling urban railway network is one of the most important parts of managing the rail transportation system. Therefore, researchers are trying to provide suitable solutions to produce an optimal timetable for the railway network. The purpose of this study is to provide a mathematical planning model to create a synchronized and optimal timetable for different lines of the railway network, including arrival time to each station and departure time from each station to reduce Travel time, waiting time at the origin station and transfer waiting time at the transfer station for passengers and maximize the number of passengers who successfully reach their destination in a specific study horizon. Stop-skipping and timetable synchronization are two effective strategies to reduce total passengers’ travel time in the urban transit network. This article proposes a mixed-integer programming model considering both strategies simultaneously. A hypothetical example was solved with GAMS (CPLEX) to evaluate the performance of the model. Since increasing the number of trains, stations, or the study horizon, exponentially increases the size of the problem, seeking efficient methods to solve real-sized problems is inevitable. A heuristic algorithm based on a genetic algorithm (GA) was developed to solve the model. Then, the results were compared with the results of GAMS. Finally, a large-scale, real-life case study based on Tehran rail transit network was used to evaluate the proposed model in this study and the genetic algorithm approach. The results indicate that the proposed model reduces each passenger’s travel time by about 1.7%, each passenger’s transfer waiting time by about 44.2% and each passenger’s in-vehicle time by about 0.55% in peak hours. And it also increases the number of passengers who successfully reach their destination by about 0.4% in peak hours.
  9. Keywords:
  10. Railway Transport ; Optimal Scheduling ; Time Dependent Origin-Destination Demand ; Urban Rail ; UrbanTransport ; Coordinated Transit Scheduling ; Train Scheduling

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