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arXiv · 2010.03983

Online Allocation of Reusable Resources via Algorithms Guided by Fluid Approximations

Vineet Goyal·Garud Iyengar·Rajan Udwani
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Abstract

We consider the problem of online allocation (matching and assortments) of reusable resources where customers arrive sequentially in an adversarial fashion and allocated resources are used or rented for a stochastic duration that is drawn independently from known distributions. Focusing on the case of large inventory, we give an algorithm that is $(1-1/e)$ competitive for general usage distributions. At the heart of our result is the notion of a relaxed online algorithm that is only subjected to fluid approximations of the stochastic elements in the problem. The output of this algorithm serves as a guide for the final algorithm. This leads to a principled approach for seamlessly addressing stochastic elements (such as reusability, customer choice, and combinations thereof) in online resource allocation problems, that may be useful more broadly.

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Vineet Goyal, Garud Iyengar, Rajan Udwani. 2020-10-08. Online Allocation of Reusable Resources via Algorithms Guided by Fluid Approximations. https://arxiv.org/abs/2010.03983

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