Data-driven resource allocation for multi-target attainment

Dohyun Ahn

European Journal of Operational Research, 2024, vol. 318, issue 3, 954-965

Abstract: We delve into a class of multi-target attainment problems, which commonly arise in practical applications such as operations management, marketing, policy making, and healthcare services. The aim is to efficiently allocate a fixed amount of resources to achieve predetermined target payoffs for multiple tasks. We transform this stochastic problem into a tractable optimization problem that, when optimized, approximately maximizes the probability of attaining all the targets as data accumulates. This transformation is leveraged to devise a batch-based resource allocation rule that demonstrates strong theoretical and numerical performance guarantees.

Keywords: Decision analysis; Target attainment; Resource allocation; Large deviations; Bandit problems (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:318:y:2024:i:3:p:954-965

DOI: 10.1016/j.ejor.2024.05.045

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