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  1. مدل مسأله زمان بندی حرکت قطارهای مترو با درنظرگرفتن تقاضای ایستگاه به ایستگاه و استفاده از استراتژی عدم توقف در همه ایستگاه ها
مدل مسأله زمان بندی حرکت قطارهای مترو با درنظرگرفتن تقاضای ایستگاه به ایستگاه و استفاده از استراتژی عدم توقف در همه ایستگاه ها
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مدل مسأله زمان بندی حرکت قطارهای مترو با درنظرگرفتن تقاضای ایستگاه به ایستگاه و استفاده از استراتژی عدم توقف در همه ایستگاه ها

جوادی نصر، محمد جواد Javadinasr, Mohammad Javad

Train Scheduling Problem using Stop-Skipping Strategy based on Stop to Stop Dependent Demand

Javadinasr, Mohammad Javad | 2019

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 51573 (19)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Shafahi, Yousef
  7. Abstract:
  8. Transit systems, especially metro lines, play a pivotal role in addressing people's mobility needs in metropolitan areas. Accordingly, incorporating policies that improve the quality of service and attract new passengers is of vital importance. In this regard, operational strategies allow for more efficient use of the transit facilities without investing a substantial amount of time and capital. In this research, the stop-skipping strategy has been evaluated by proposing a mathematical optimization model with the aim of improving passengers' waiting and in-vehicle times, representing users' cost, along with trains running times, representing the transit company's cost. The decision variables of the model determine to stop or to move of trains in each station. Since increasing the number of trains or stations, exponentially increase the size of the problem, seeking practical methods to address real-sized problems was a must. Considering the discrete nature of decision variables, the Ant Colony Algorithm was assessed to solve the model. As a case study, line 1 of the Tehran metro network was chosen to evaluate the proposed model and the solving method. Utilizing the data gathered in the automated fare collection system from 21/4/2018 to 21/5/2018, the origin-destination station demand of passengers was estimated and used to evaluate the model. The results of solving the model for the peak hour indicated that incorporating stop-skipping strategy at line 1 of Tehran Metro network, approximately decreased the passengers' waiting times by 12 percent, passengers' in-vehicle times by 5 percent, and trains running times by 3 percent, in comparison to the all-stop strategy
  9. Keywords:
  10. Metro Scheduling ; Ant Colony Algorithm ; Stop-Skipping Strategy ; Smart Fare Collection Card ; Train Scheduling ; Metro Activity

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