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A Black-Box Approach for Exogenous Replenishment in Online Resource Allocation

Published: July 20, 2025 | arXiv ID: 2507.14812v1

By: Suho Kang, Ziyang Liu, Rajan Udwani

BigTech Affiliations: University of California, Berkeley

Potential Business Impact:

Makes online selling work better with new stock.

In a typical online resource allocation problem, we start with a fixed inventory of resources and make online allocation decisions in response to resource requests that arrive sequentially over a finite horizon. We consider settings where the inventory is replenished over time according to an unknown exogenous process. We introduce black-box methods that extend any existing algorithm, originally designed without considering replenishment, into one that works with an arbitrary (adversarial or stochastic) replenishment process. Our approach preserves the original algorithm's competitive ratio in regimes with large initial inventory, thereby enabling the seamless integration of exogenous replenishment into a large body of existing algorithmic results for both adversarial and stochastic arrival models.

Country of Origin
🇺🇸 United States

Page Count
31 pages

Category
Computer Science:
Data Structures and Algorithms