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Ride-matching and routing optimisation: Models and a large neighbourhood search heuristic

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  • Hou, Liwen
  • Li, Dong
  • Zhang, Dali

Abstract

This paper considers a ridesharing problem on how to match riders to drivers and how to choose the best routes for vehicles. Unlike the others in the literature, we are concerned with the maximization of the average loading ratio of the entire system. Moreover, we develop a flow-dependent version of the model to characterize the impact of pick-up and drop-off congestion. In another extended model we take into account the riders’ individual evaluation on different transportation modes. Due to the large size of the resulting models, we develop a large neighbourhood search algorithm and demonstrate its efficiency.

Suggested Citation

  • Hou, Liwen & Li, Dong & Zhang, Dali, 2018. "Ride-matching and routing optimisation: Models and a large neighbourhood search heuristic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 143-162.
    • Handle: RePEc:eee:transe:v:118:y:2018:i:c:p:143-162
    DOI: 10.1016/j.tre.2018.07.003
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    4. Hua, Shijia & Zeng, Wenjia & Liu, Xinglu & Qi, Mingyao, 2022. "Optimality-guaranteed algorithms on the dynamic shared-taxi problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    5. Sun, Yanshuo & Chen, Zhi-Long & Zhang, Lei, 2020. "Nonprofit peer-to-peer ridesharing optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
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    8. Le, Tho V. & Ukkusuri, Satish V. & Xue, Jiawei & Van Woensel, Tom, 2021. "Designing pricing and compensation schemes by integrating matching and routing models for crowd-shipping systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
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    11. Bian, Zheyong & Liu, Xiang, 2019. "Mechanism design for first-mile ridesharing based on personalized requirements part I: Theoretical analysis in generalized scenarios," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 147-171.

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