UAI 2022poster2 citations
Dynamic relocation in ridesharing via fixpoint construction
Ian A. Kash, Zhongkai Wen, Lenore D. Zuck
Abstract
To address spatial imbalances in the supply and demand of drivers, ridesharing platforms can make use of policies to direct driver relocation. We study a simple model of this problem, which allows us to give a constructive characterization of the unique fixpoint of system dynamics. Using this construction, we design a dynamic policy that provides stronger, than previous work, guarantees about its rate of convergence to the fixpoint. Simulations demonstrate the benefits of our approach.
BibTeX
@InProceedings{pmlr-v180-kash22a,
title = {Dynamic relocation in ridesharing via fixpoint construction },
author = {Kash, Ian A. and Wen, Zhongkai and Zuck, Lenore D.},
booktitle = {Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence},
pages = {980--989},
year = {2022},
editor = {Cussens, James and Zhang, Kun},
volume = {180},
series = {Proceedings of Machine Learning Research},
month = {01--05 Aug},
publisher = {PMLR},
pdf = {https://proceedings.mlr.press/v180/kash22a/kash22a.pdf},
url = {https://proceedings.mlr.press/v180/kash22a.html},
abstract = {To address spatial imbalances in the supply and demand of drivers, ridesharing platforms can make use of policies to direct driver relocation. We study a simple model of this problem, which allows us to give a constructive characterization of the unique fixpoint of system dynamics. Using this construction, we design a dynamic policy that provides stronger, than previous work, guarantees about its rate of convergence to the fixpoint. Simulations demonstrate the benefits of our approach.}
}