Publication Type
Journal Article
Version
publishedVersion
Publication Date
2-2017
Abstract
Bike Sharing Systems (BSSs) are widely adopted in major cities of the world due to concerns associated with extensive private vehicle usage, namely, increased carbon emissions, traffic congestion and usage of nonrenewable resources. In a BSS, base stations are strategically placed throughout a city and each station is stocked with a pre-determined number of bikes at the beginning of the day. Customers hire the bikes from one station and return them at another station. Due to unpredictable movements of customers hiring bikes, there is either congestion (more than required) or starvation (fewer than required) of bikes at base stations. Existing data has shown that congestion/starvation is a common phenomenon that leads to a large number of unsatisfied customers resulting in a significant loss in customer demand. In order to tackle this problem, we propose an optimisation formulation to reposition bikes using vehicles while also considering the routes for vehicles and future expected demand. Furthermore, we contribute two approaches that rely on decomposability in the problem (bike repositioning and vehicle routing) and aggregation of base stations to reduce the computation time significantly. Finally, we demonstrate the utility of our approach by comparing against two benchmark approaches on two real-world data sets of bike sharing systems. These approaches are evaluated using a simulation where the movements of customers are generated from real-world data sets.
Keywords
Bicycles, Shared mobility systems, routing problem, optimization
Discipline
Artificial Intelligence and Robotics | Computer Sciences | Operations Research, Systems Engineering and Industrial Engineering | Transportation
Research Areas
Intelligent Systems and Optimization
Publication
Journal of Artificial Intelligence Research
Volume
58
First Page
387
Last Page
430
ISSN
1076-9757
Identifier
10.1613/jair.5308
Publisher
Association for the Advancement of Artificial Intelligence / AI Access Foundation
Citation
GHOSH, Supriyo; VARAKANTHAM, Pradeep; ADULYASAK, Yossiri; and JAILLET, Patrick.
Dynamic repositioning to reduce lost demand in Bike Sharing Systems. (2017). Journal of Artificial Intelligence Research. 58, 387-430.
Available at: https://ink.library.smu.edu.sg/sis_research/3688
Copyright Owner and License
Publisher
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1613/jair.5308
Included in
Artificial Intelligence and Robotics Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Transportation Commons