Joint Operating Revenue and Passenger Travel Cost Optimization in Urban Rail Transit
Joint Operating Revenue and Passenger Travel Cost Optimization in Urban Rail Transit
- New search for: Wenxin Li
- New search for: Qiyuan Peng
- New search for: Qinlin Li
- New search for: Chao Wen
- New search for: Yongxiang Zhang
- New search for: Javad Lessan
- New search for: Wenxin Li
- New search for: Qiyuan Peng
- New search for: Qinlin Li
- New search for: Chao Wen
- New search for: Yongxiang Zhang
- New search for: Javad Lessan
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.
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Joint Operating Revenue and Passenger Travel Cost Optimization in Urban Rail Transit
2018
Article (Journal)
Electronic Resource
Unknown
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