Online Repositioning in Bike Sharing Systems
Name
icaps17-bikeshare.pdf
Description
Accepted version
Size
396.26 KB
Format
Adobe PDF
Checksum (MD5)
e9ca9426de41b90144b895585a7070aa
Author(s)
Lowalekar, Meghna
Varakantham, Pradeep
Ghosh, Supriyo
Jena, Sanjay Dominik
Jaillet, Patrick
Date Issued
2017
Publisher
AAAI
Citation
Lowalekar, Meghna, Varakantham, Pradeep, Ghosh, Supriyo, Jena, Sanjay Dominik and Jaillet, Patrick. 2017. "Online Repositioning in Bike Sharing Systems."
Version
Author's final manuscript
Abstract
Copyright © 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. Due to increased traffic congestion and carbon emissions, Bike Sharing Systems (BSSs) are adopted in various cities for short distance travels, specifically for last mile transportation. The success of a bike sharing system depends on its ability to have bikes available at the "right" base stations at the "right" times. Typically, carrier vehicles are used to perform repositioning of bikes between stations so as to satisfy customer requests. Owing to the uncertainty in customer demand and day-long repositioning, the problem of having bikes available at the right base stations at the right times is a challenging one. In this paper, we propose a multi-stage stochastic formulation, to consider expected future demand over a set of scenarios to find an efficient repositioning strategy for bike sharing systems. Furthermore, we provide a Lagrangian decomposition approach (that decouples the global problem into routing and repositioning slaves and employs a novel DP approach to efficiently solve routing slave) and a greedy online anticipatory heuristic to solve large scale problems effectively and efficiently. Finally, in our experimental results, we demonstrate significant reduction in lost demand provided by our techniques on real world datasets from two bike sharing companies in comparison to existing benchmark approaches.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
http://icaps17.icaps-conference.org/papers.html
