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Data-driven resource allocation for multi-target attainment

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  • Ahn, Dohyun

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.

Suggested Citation

  • Ahn, Dohyun, 2024. "Data-driven resource allocation for multi-target attainment," European Journal of Operational Research, Elsevier, vol. 318(3), pages 954-965.
    • Handle: RePEc:eee:ejores:v:318:y:2024:i:3:p:954-965
    DOI: 10.1016/j.ejor.2024.05.045
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    References listed on IDEAS

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