Trading Utility for Dynamic Fairness in Multiple Resource Division with Sequential Demand
Dynamic multi-resource allocation is a central problem in shared computing environments, where users' demands arrive sequentially and resources must be distributed fairly without knowledge of future demands. Existing methods emphasize fairness guarantees such as Sharing Incentive, Envy Freeness, and Dynamic Pareto Optimality, but often overlook system utility. Moreover, these fairness criteria are mutually incompatible, preventing strict enforcement of them at the same time. We propose a neural allocation mechanism that reconciles fairness with utility through multi-objective optimization during sequential rollout. We first formalize fairness in the dynamic setting via stepwise loss funct...
| Authors | Kaiqi Jiang, Karim El Husseini, Wenzhe Fan et al. |
|---|---|
| Primary category | cs.GT |
| Published | 9 June 2026 |
| Last updated at source | 9 June 2026 |
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