Bus timetable optimization model in response to the diverse and uncertain requirements of passengers for travel comfort

Peiqun Lin; Chenxing He; Lingshu Zhong; Mingyang Pei; Chuhao Zhou; Yang Liu; Peiqun Lin; Chenxing He; Lingshu Zhong; Mingyang Pei; Chuhao Zhou; Yang Liu

doi:10.3934/era.2023118

Electronic Research Archive

2023, Volume 31, Issue 4: 2315-2336. doi: 10.3934/era.2023118

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Bus timetable optimization model in response to the diverse and uncertain requirements of passengers for travel comfort

1.
School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China
2.
School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, China
3.
Department of Architecture and Civil Engineering, Chalmers University of Technology, Gothenburg SE-412 96, Sweden

Received: 25 November 2022 Revised: 17 February 2023 Accepted: 21 February 2023 Published: 24 February 2023

Most existing public transit systems have a fixed dispatching and service mode, which cannot effectively allocate resources from the perspective of the interests of all participants, resulting in resource waste and dissatisfaction. Low passenger satisfaction leads to a considerable loss of bus passengers and further reduces the income of bus operators. This study develops an optimization model for bus schedules that considers vehicle types and offers two service levels based on heterogeneous passenger demands. In this process, passenger satisfaction, bus company income, and government subsidies are considered. A bilevel model is proposed with a lower-level passenger ride simulation model and an upper-level multiobjective optimization model to maximize the interests of bus companies, passengers, and the government. To verify the effectiveness of the proposed methodology, a real-world case from Guangzhou is presented and analyzed using the nondominated sorting genetic algorithm-Ⅱ (NSGA-Ⅱ), and the related Pareto front is obtained. The results show that the proposed bus operation system can effectively increase the benefits for bus companies, passengers, and the government.
- bus timetable,
- multiple service levels,
- pareto front,
- nondominated sorting genetic algorithm-Ⅱ
Citation: Peiqun Lin, Chenxing He, Lingshu Zhong, Mingyang Pei, Chuhao Zhou, Yang Liu. Bus timetable optimization model in response to the diverse and uncertain requirements of passengers for travel comfort[J]. Electronic Research Archive, 2023, 31(4): 2315-2336. doi: 10.3934/era.2023118

Related Papers:

Abstract

Most existing public transit systems have a fixed dispatching and service mode, which cannot effectively allocate resources from the perspective of the interests of all participants, resulting in resource waste and dissatisfaction. Low passenger satisfaction leads to a considerable loss of bus passengers and further reduces the income of bus operators. This study develops an optimization model for bus schedules that considers vehicle types and offers two service levels based on heterogeneous passenger demands. In this process, passenger satisfaction, bus company income, and government subsidies are considered. A bilevel model is proposed with a lower-level passenger ride simulation model and an upper-level multiobjective optimization model to maximize the interests of bus companies, passengers, and the government. To verify the effectiveness of the proposed methodology, a real-world case from Guangzhou is presented and analyzed using the nondominated sorting genetic algorithm-Ⅱ (NSGA-Ⅱ), and the related Pareto front is obtained. The results show that the proposed bus operation system can effectively increase the benefits for bus companies, passengers, and the government.

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