Journal of Transportation Research

Journal of Transportation Research

A Stochastic Train Timetabling Mathematical Model to Minimize the Passengers Travel Time (Case Study: Tehran Metro)

Document Type : Original Article

Authors
Zeinab Hajizamani 1
Hamed Ashenaei 2
Hadi Sahebi 3
1 Ph.D., Student, School of Management, Economics and Progress Engineering, Iran University of Science and Technology, Tehran, Iran.
2 M.Sc. Student, School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.
3 Associate Professor, School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.
10.22034/tri.2021.259577.2841
Abstract
One of the most significant aspects of train timetable optimization is determining the arrival dwell time in the subway system. A good timetable improves the efficiency of trains and resources, reducing passenger wait times. This study provides a timetable optimization model to reduce passenger journey time. In this model, train movement between two stations is divided into three phases: accelerating, coasting, and breaking, with random numbers used for running duration in each phase due to stochastic delays in crowded stations. First, we develop a stochastic integer programming model that includes headway and dwell time. The Scenario-Based Uncertain Programming Approach is then utilized to simplify. Finally, numerical examples are provided for Tehran's metro system. The model's optimal solution is determined via a genetic algorithm. The results demonstrate that the model can lower the passenger waiting time when compared to the current timetable.
Keywords
Subway System
Train Timetabling
Stochastic Optimization
Passenger Travel Time
Genetic Algorithm
Subjects
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