Title: An optimisation model of time-of-use pricing for ride-hailing platforms

Authors: Wei Zhang; Shujing Wan

Addresses: School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou, China

Abstract: For the problem of online ride-hailing market pricing, time-of-use pricing plan on ride-hailing platform is studied in this paper, considering the interests of the platform, drivers and passengers. Firstly, the multi-objective optimisation model of time-of-use pricing is built, in which the different price coefficients are used in peak hours and off-peak hours. The method of determining the drivers-passenger matching quantity is proposed. Then the algorithm solving the model is designed based on non-dominated sorting genetic algorithms. Finally, the validity of the time-of-use pricing method proposed in this paper is verified by a case study, and the relevant rules of time-of-use pricing are analysed. The research shows that the method can effectively improve the interests of the platform, driver and passenger. The revenues of the platform and driver can be increased by 12.9% and 4.15%, respectively, and the passenger payment can be saved by 8.64% at most relative to single price.

Keywords: urban traffic; time-of-use pricing; multi-objective optimisation; online ride-hailing; genetic algorithm.

DOI: 10.1504/IJADS.2025.145887

International Journal of Applied Decision Sciences, 2025 Vol.18 No.3, pp.360 - 381

Received: 15 Oct 2023
Accepted: 10 Jan 2024
Published online: 30 Apr 2025 *

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