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Communication Dans Un Congrès Année : 2022

A Shareability Clustering Method to Solve the Dynamic Ride-Sharing Problem Considering Network Congestion

Résumé

One of the most challenging facets of dynamic ride-sharing problems is the automated matching process, especially in large-scale networks where the number of received requests is huge. Matching users to trips is very challenging in real-time since it must happen very quickly while it must ensure high quality solutions. In this paper, we rely on an exact solving method to ensure the quality of the solution, while using AI-based techniques to limit the number of requests that we feed to the solver. More precisely, we propose a clustering method based on a new space-time shareability function to put the most shareable trips inside separate clusters. Each cluster is then managed with a proposed heuristic framework in order to solve the matching problem inside each cluster. To validate our proposal, we employ the proposed method on the network of Lyon city in France, with half-million requests in the morning peak from 6 to 10 AM. The results demonstrate that the algorithm can provide high-quality solutions in a short time for large-scale problems.
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Dates et versions

hal-03680835 , version 1 (29-05-2022)

Identifiants

  • HAL Id : hal-03680835 , version 1

Citer

Negin Alisoltani, Mostafa Ameli, Mahdi Zargayouna, Ludovic Leclercq. A Shareability Clustering Method to Solve the Dynamic Ride-Sharing Problem Considering Network Congestion. TRB 2022, Transportation Research Board 101st Annual Meeting, Jan 2022, Washington, D.C, United States. ⟨hal-03680835⟩
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