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

ABSTRACT

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.

KEYWORDS:

• Bike-sharing system
• repositioning
• hierarchical clustering
• coordinated stations
• heuristics

Acknowledgments

This work was partially supported by the National Natural Science Foundation of China [Grant Nos. 71772002, 71774145].

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [71774145]; National Natural Science Foundation of China [71772002].