Sequential Fair Allocation With Replenishments: A Little Envy Goes An Exponentially Long Way

Fuente: arXiv
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Autori principali: Onyeze, Chido, Sinclair, Sean R., Hssaine, Chamsi, Banerjee, Siddhartha
Natura: Preprint
Pubblicazione: 2025
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author Onyeze, Chido
Sinclair, Sean R.
Hssaine, Chamsi
Banerjee, Siddhartha
author_facet Onyeze, Chido
Sinclair, Sean R.
Hssaine, Chamsi
Banerjee, Siddhartha
contents We study the trade-off between envy and inefficiency in repeated resource allocation settings with stochastic replenishments, motivated by real-world systems such as food banks and medical supply chains. Specifically, we consider a model in which a decision-maker faced with stochastic demand and resource donations must trade off between an equitable and efficient allocation of resources over an infinite horizon. The decision-maker has access to storage with fixed capacity $M$, and incurs efficiency losses when storage is empty (stockouts) or full (overflows). We provide a nearly tight (up to constant factors) characterization of achievable envy-inefficiency pairs. Namely, we introduce a class of Bang-Bang control policies whose inefficiency exhibits a sharp phase transition, dropping from $Θ(1/M)$ when $Δ= 0$ to $e^{-Ω(ΔM)}$ when $Δ> 0$, where $Δ$ is used to denote the target envy of the policy. We complement this with matching lower bounds, demonstrating that the trade-off is driven by supply, as opposed to demand uncertainty. Our results demonstrate that envy-inefficiency trade-offs not only persist in settings with dynamic replenishment, but are shaped by the decision-maker's available capacity, and are therefore qualitatively different compared to previously studied settings with fixed supply.
format Preprint
id arxiv_https___arxiv_org_abs_2508_21753
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Sequential Fair Allocation With Replenishments: A Little Envy Goes An Exponentially Long Way
Onyeze, Chido
Sinclair, Sean R.
Hssaine, Chamsi
Banerjee, Siddhartha
Optimization and Control
Computer Science and Game Theory
Probability
We study the trade-off between envy and inefficiency in repeated resource allocation settings with stochastic replenishments, motivated by real-world systems such as food banks and medical supply chains. Specifically, we consider a model in which a decision-maker faced with stochastic demand and resource donations must trade off between an equitable and efficient allocation of resources over an infinite horizon. The decision-maker has access to storage with fixed capacity $M$, and incurs efficiency losses when storage is empty (stockouts) or full (overflows). We provide a nearly tight (up to constant factors) characterization of achievable envy-inefficiency pairs. Namely, we introduce a class of Bang-Bang control policies whose inefficiency exhibits a sharp phase transition, dropping from $Θ(1/M)$ when $Δ= 0$ to $e^{-Ω(ΔM)}$ when $Δ> 0$, where $Δ$ is used to denote the target envy of the policy. We complement this with matching lower bounds, demonstrating that the trade-off is driven by supply, as opposed to demand uncertainty. Our results demonstrate that envy-inefficiency trade-offs not only persist in settings with dynamic replenishment, but are shaped by the decision-maker's available capacity, and are therefore qualitatively different compared to previously studied settings with fixed supply.
title Sequential Fair Allocation With Replenishments: A Little Envy Goes An Exponentially Long Way
topic Optimization and Control
Computer Science and Game Theory
Probability
url https://arxiv.org/abs/2508.21753