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A Restless Bandit Model for Resource Allocation, Competition, and Reservation

journal contribution
posted on 2022-09-29, 01:29 authored by J Fu, Bill Moran, P G Taylor
We study a resource allocation problem with varying requests and with resources of limited capacity shared by multiple requests. It is modeled as a set of heterogeneous restless multiarmed bandit problems (RMABPs) connected by constraints imposed by resource capacity. Following Whittle's relaxation idea and Weber and Weiss' asymptotic optimality proof, we propose a simple policy and prove it to be asymptotically optimal in a regime where both arrival rates and capacities increase. We provide a simple sufficient condition for asymptotic optimality of the policy and, in complete generality, propose a method that generates a set of candidate policies for which asymptotic optimality can be checked. The effectiveness of these results is demonstrated by numerical experiments. To the best of our knowledge, this is the first work providing asymptotic optimality results for such a resource allocation problem and such a combination of multiple RMABPs. Copyright:

History

Journal

Operations Research

Volume

70

Issue

1

Pagination

416 - 431

ISSN

0030-364X

eISSN

1526-5463

Publication classification

C1.1 Refereed article in a scholarly journal

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