Robust knapsack ordering for a partially-informed newsvendor with budget constraint

This paper studies a robust version of the multi-item newsvendor problem with limited budget. The demand distribution belongs to an ambiguity set that contains all distributions that share the same range, mean and mean absolute deviation. The resulting optimization problem turns out to be solvable by a method reminiscent of the greedy algorithm for continuous knapsack problems, purchasing items in order of marginal effect on the total cost until the budget is spent.