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Collaborative optimization for train stop planning and train timetabling on high-speed railways based on passenger

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Area of Science:

  • Operations Research
  • Transportation Science
  • Railway Engineering

Background:

  • Rapid development of high-speed railways (HSR) driven by increasing passenger demand.
  • Critical importance of efficient stop planning and timetabling for HSR operations and passenger experience.
  • Existing challenges in optimizing complex HSR networks.

Purpose of the Study:

  • To develop a collaborative optimization approach for HSR stop planning and timetabling.
  • To minimize total passenger travel time and total train travel time.
  • To reduce deviations in train departure times.

Main Methods:

  • A two-phase optimization strategy.
  • Phase 1: Mixed-integer nonlinear programming for stop plan optimization, considering passenger OD demand, train capacity, and stop frequency.
  • Phase 2: Multiobjective mixed-integer linear programming for timetable optimization, incorporating train types and refined headways.

Main Results:

  • Application to China's HSR network using the GUROBI optimizer.
  • Achieved a 2.81% reduction in total passenger travel time.
  • Achieved a 3.34% reduction in total train travel time.

Conclusions:

  • The proposed collaborative optimization approach effectively enhances HSR operational efficiency.
  • The method provides a more efficient solution for integrated stop planning and timetabling.
  • Demonstrates significant improvements in travel times for both passengers and trains.