Space-time clustering-based method to optimize shareability in real-Time Ride-Sharing - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue PLoS ONE Année : 2022

Space-time clustering-based method to optimize shareability in real-Time Ride-Sharing

Résumé

Real-time ride-sharing has become popular in recent years. However, the underlying optimization problem for this service is highly complex. One of the most critical challenges when solving the problem is solution quality and computation time, especially in large-scale problems where the number of received requests is huge. 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 shareability function to put the most shareable trips inside separate clusters. Previous studies only consider Spatio-temporal dependencies to do clustering on the mobility service requests, which is not efficient in finding the shareable trips. Here, we define the shareability function to consider all the different sharing states for each pair of trips. Each cluster is then managed with a proposed heuristic framework in order to solve the matching problem inside each cluster. As the method favors sharing, we present the number of sharing constraints to allow the service to choose the number of shared trips. 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. The proposed clustering method can also be used for different mobility service problems such as car-sharing, bike-sharing, etc.
Fichier principal
Vignette du fichier
doc00035317.pdf (2.07 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-03794709 , version 1 (03-10-2022)

Identifiants

Citer

Negin Alisoltani, Mostafa Ameli, Mahdi Zargayouna, Ludovic Leclercq. Space-time clustering-based method to optimize shareability in real-Time Ride-Sharing. PLoS ONE, 2022, 17 (1), pp.e0262499. ⟨10.1371/journal.pone.0262499⟩. ⟨hal-03794709⟩
39 Consultations
19 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More