Joint Operating Revenue and Passenger Travel Cost Optimization in Urban Rail Transit

Wenxin Li,Yongxiang Zhang,Chao Wen,Qiyuan Peng,Javad Lessan,Qinlin Li

doi:10.1155/2018/7805168

Wenxin Li, Yongxiang Zhang + Show 4 more

Open Access

https://doi.org/10.1155/2018/7805168

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Abstract

Urban rail transit (URT) scheduling requires designing efficient timetables that can meet passengers’ expectations about the lower travel cost while attaining revenue management objectives of the train operators. This paper presents a biobjective timetable optimization model that seeks maximizing the operating revenue of the railway company while lowering passengers’ average travel cost. We apply a fuzzy multiobjective optimization and a nondominated sorting genetic algorithm II to solve the optimization problem and characterize the trade-off between the conflicting objective functions under different types of distances. To illustrate the model and solution methodology, the proposed model and solution algorithms are validated against train operation record from a URT line of Chengdu metro in China. The results show that significant improvements can be achieved in terms of the travel cost and revenue return criteria when implementing the solutions obtained by the proposed model.

Highlights

Being fast, reliable, safe, and convenient, Urban rail transit (URT) has been able to provide satisfactory trip services and mitigate urban traffic congestion in Metropolitan cities, e.g., Tokyo [1], Beijing [2], and New York [3]
The optimization results show that when the weight of the operating revenue is as important as the average travel cost of the passengers in the objective function (i.e., λ1 = λ2 = 0.5), the optimal speed (V) is 18.3m/s
The objectives are to maximize the revenue of the system planner who operates trains while trying to minimize the average travel costs of the passengers

Summary

Introduction

Reliable, safe, and convenient, URT has been able to provide satisfactory trip services and mitigate urban traffic congestion in Metropolitan cities, e.g., Tokyo [1], Beijing [2], and New York [3]. An operating timetable should consider both passengers’ point of view and operators’ objectives In this regard, the New Haven line of the Metro-North Commuter Railroad can be mentioned as a real-world case where minimizing energy consumption in track alignment, speed limit, and schedule adherence objectives are considered to satisfy passengers and operators expectations simultaneously [6]. The New Haven line of the Metro-North Commuter Railroad can be mentioned as a real-world case where minimizing energy consumption in track alignment, speed limit, and schedule adherence objectives are considered to satisfy passengers and operators expectations simultaneously [6] In another effort, to obtain energy-efficient train operations and distribute the total trip time among different sections, a numerical algorithm is proposed in [7].

Literature Review

Biobjective Optimization Model

Solution Approaches

Numerical Experiments

Conclusions