Optimizing Online Knapsack Allocation with Time Fairness Guarantees

This work formalizes a notion of time fairness for the online knapsack problem, where the probability of an item being accepted depends only on its value density and not its arrival time. It proposes deterministic and learning-augmented algorithms that achieve a Pareto-optimal trade-off between fairness and competitiveness.