Train scheduling for minimizing passenger waiting time with time-dependent demand and skip-stop patterns: Nonlinear integer programming models with linear constraints

Huimin Niu, Xuesong Zhou and Ruhu Gao

Transportation Research Part B: Methodological, 2015, vol. 76, issue C, 117-135

Abstract: This paper focuses on how to minimize the total passenger waiting time at stations by computing and adjusting train timetables for a rail corridor with given time-varying origin-to-destination passenger demand matrices. Given predetermined train skip-stop patterns, a unified quadratic integer programming model with linear constraints is developed to jointly synchronize effective passenger loading time windows and train arrival and departure times at each station. A set of quadratic and quasi-quadratic objective functions are proposed to precisely formulate the total waiting time under both minute-dependent demand and hour-dependent demand volumes from different origin–destination pairs. We construct mathematically rigorous and algorithmically tractable nonlinear mixed integer programming models for both real-time scheduling and medium-term planning applications. The proposed models are implemented using general purpose high-level optimization solvers, and the model effectiveness is further examined through numerical experiments of real-world rail train timetabling test cases.

Keywords: Train timetable; Passenger waiting time; Time-varying demand; Skip-stop pattern; Nonlinear mixed integer programming (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (95)

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DOI: 10.1016/j.trb.2015.03.004

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