Most previous research on bike-sharing repositioning problem (BRP) tends to apply backup bikes from depot rather than employ non-repositioning stations, which not only leads to underutilization of resources but also increases repositioning cost. To address this issue, we propose a bike-sharing repositioning model in this paper, and then design an improved hierarchical clustering algorithm which takes into account both the total amount of repositioning and the number of stations within a cluster, thus greatly reducing the problem complexity in large-scale cases. Based on the clustering results, we presented two methods which consider global and local self-balancing intra-cluster repositioning amount (SIRA) to perform repositioning, respectively. Performance of our methods is validated on four instances, and a large number of comparative experiments with Gourbi as well as state-of-the-art algorithms are conducted, which demonstrate that the proposed methods are highly competitive in solving BRPs, especially large BRPs comprising more problem stations.


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    Titel :

    Solving the bike-sharing repositioning problem considering coordination stations based on self-balancing and clustering strategies


    Beteiligte:
    Cao, Jianhua (Autor:in) / Xu, Weixiang (Autor:in) / Wang, Wenzheng (Autor:in) / Pan, Ruilin (Autor:in) / Zhou, Chunliu (Autor:in)

    Erschienen in:

    Transportation Letters ; 15 , 8 ; 1025-1042


    Erscheinungsdatum :

    14.09.2023


    Format / Umfang :

    18 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt






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