Pricing and Optimization in Shared Vehicle Systems: An Approximation Framework
Name
1608.06819.pdf
Description
Accepted version
Size
509.47 KB
Format
Adobe PDF
Checksum (MD5)
b85b83cd8b963f4008422fcac5585e14
Author(s)
Banerjee, Siddhartha
Freund, Daniel
Lykouris, Thodoris
Date Issued
2021
Journal
Operations Research
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Citation
Banerjee, Siddhartha, Freund, Daniel and Lykouris, Thodoris. 2021. "Pricing and Optimization in Shared Vehicle Systems: An Approximation Framework." Operations Research, 70 (3).
Version
Author's final manuscript
Abstract
The optimal management of shared vehicle systems, such as bike-, scooter-, car-, or ride-sharing, is more challenging compared with traditional resource allocation settings because of the presence of spatial externalities—changes in the demand/supply at any location affect future supply throughout the system within short timescales. These externalities are well captured by steady-state Markovian models, which are therefore widely used to analyze such systems. However, using Markovian models to design pricing and other control policies is computationally difficult because the resulting optimization problems are high dimensional and nonconvex. In our work, we design a framework that provides near-optimal policies, for a range of possible controls, that are based on applying the possible controls to achieve spatial balance on average. The optimality gap of these policies improves as the ratio between supply and the number of locations increases and asymptotically goes to zero.
MIT Department
Sloan School of Management
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1287/OPRE.2021.2165
