Develops polynomial-time algorithms achieving competitive ratios of ~1/14.85 (general) and 1/6.86 (unit costs) for submodular welfare maximization with budgets under random-order item arrival.
Improved online algorithms for knapsack and GAP in the random order model.Algorithmica, 83(6):1750–1785, 2021
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Submodular Welfare Maximization with Budget Constraints in the Random-Order Model
Develops polynomial-time algorithms achieving competitive ratios of ~1/14.85 (general) and 1/6.86 (unit costs) for submodular welfare maximization with budgets under random-order item arrival.