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ICTD 2025

Transportation Planning

POSTER RECEPTION (View list of posters here)

Research on Online Bus-Hailing Route Planning Based on a Bi-level Programming Model

Tuesday, June 10, 2025
4:45 PM – 6:00 PM MT

    Co-Author(s)

  • ZY

    Zijuan Yin, PhD (she/her/hers)

    n/a
    Southeast University
    Nanjing, Jiangsu, China (People's Republic)

    • Presenter(s)

  • ZY

    Zijuan Yin, PhD (she/her/hers)

    n/a
    Southeast University
    Nanjing, Jiangsu, China (People's Republic)

    • Co-Author(s)

  • YG

    Yichen Gu, n/a

    No.2 Southeast University Road, Nanjing, Jiangsu, China
    Southeast University
    Nanjing, Jiangsu, China (People's Republic)

  • YZ

    Yan Zheng, n/a

    No.2 Southeast University Road, Nanjing, Jiangsu, China
    Southeast University
    Nanjing, Jiangsu, China (People's Republic)

    • Primary Author(s)

  • WL

    Wenquan Li, n/a

    No.2 Southeast University Road, Nanjing, Jiangsu, China
    Southeast University
    Nanjing, Jiangsu, China (People's Republic)

    • Co-Author(s)

  • WL

    Wenquan Li, n/a

    No.2 Southeast University Road, Nanjing, Jiangsu, China
    Southeast University
    Nanjing, Jiangsu, China (People's Republic)

    • Submitter(s)

  • ZY

    Zijuan Yin, PhD (she/her/hers)

    n/a
    Southeast University
    Nanjing, Jiangsu, China (People's Republic)

Abstract: Online bus-hailing service is a transportation method that allows users to book rides via an online platform, providing flexible and efficient services. It combines the demand-responsive and timely service features of ride-hailing with the low cost, low fare, and high capacity advantages of public transit. Despite the growing prominence of online bus-hailing, research on its operational route planning is limited. On one hand, while the effectiveness of combining various heuristic algorithms with greedy algorithms has been validated, the integration of other heuristic algorithms remains under-researched. On the other hand, existing literature lacks studies incorporating accessibility measures into route planning models. Therefore, there are challenges in studying online bus-hailing route planning: first, to validate the feasibility and effectiveness of combining other heuristic algorithms with greedy algorithms; second, to explore the potential and applicability of incorporating accessibility measures into route planning models. To address these challenges, this paper aims to construct a bi-level programming model with the goal of maximizing accessibility, and design a solution algorithm that combines greedy algorithms with particle swarm optimization (PSO) algorithm to ultimately derive operational strategies for online bus-hailing. This study provides guidance for the reasonable implementation of online bus-hailing service from the perspectives of both passengers and operators.

Learning Objectives:

Attendees can expect to learn the following from this session:
  • Upon completion, participant will be able to validate the feasibility and effectiveness of combining particle swarm optimization (PSO) algorithm with greedy algorithms.
  • Upon completion, participant will be able to explore the potential and applicability of incorporating accessibility measures into route planning models.
  • Upon completion, participant will be able to derive operational strategies for online bus-hailing.