Scholarlink

We study a large-scale dial-a-ride system considering around 300, 000 dynamic requests. An efficient routing algorithm is crucial to guaranteeing the viability of the system. Large-scale requests are assumed to be dominated by daily commuting needs and thus should exhibit similar mobility patterns from one day to another. Consequently, daily vehicle trajectories should also be recurring if similar requests can be served in the same manner. We introduce a greedy insertion algorithm integrating a Guided Insertion Mechanism that learns insertion patterns from reference resolution to enhance the operational efficiency of the underlined systems while maintaining high-quality solutions.

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Learning Insertion Patterns to Enhance Operational Efficiency in Large-Scale Dial-a-Ride Systems

  • 会议论文

  • 发表日期：

    2025年

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  • Chijia Liu,
  • Alain Quilliot,
  • Hélène Toussaint,
  • Dominique Feillet

摘要

We study a large-scale dial-a-ride system considering around 300, 000 dynamic requests. An efficient routing algorithm is crucial to guaranteeing the viability of the system. Large-scale requests are assumed to be dominated by daily commuting needs and thus should exhibit similar mobility patterns from one day to another. Consequently, daily vehicle trajectories should also be recurring if similar requests can be served in the same manner. We introduce a greedy insertion algorithm integrating a Guided Insertion Mechanism that learns insertion patterns from reference resolution to enhance the operational efficiency of the underlined systems while maintaining high-quality solutions.