Minimax Analysis for Finite-horizon Inventory Models

We consider stochastic finite-horizon inventory models with discrete distributions that are incompletely specified by selected moments, percentiles, or a combination of moments and percentiles. The objective is to determine an inventory policy that minimizes the maximum expected cost over the class of demand distributions satisfying the specifications described above. We show that many inventory models of this form can be solved by a sequence of linear programs.