Motivated by a major private health insurance payer in the U.S., this paper develops a decision support model to better control healthcare expenditure and maximize payer profit through Provider Network Selection and Patient Targeting (PNSPT). The PNSPT problem involves jointly deciding which...

We generalise polyhedral projection (Fourier-Motzkin elimination) to integer programming (IP) and derive from this an alternative perspective on IP that parallels the classical theory. We first observe that projection of an IP yields an IP augmented with linear congruence relations and...

Geographical considerations such as contiguity and compactness are necessary elements of political districting in practice. Yet an analysis of the problem without such constraints yields mathematical insights that can inform real-world model construction. In particular, it clarifies the sharp...

We study the problem when a firm sets prices for products based on the transaction data, i.e., which product past customers chose from an assortment and what were the historical prices that they observed. Our approach does not impose a model on the distribution of the customers’ valuations and...

Operational models often balance assignment and capacity decisions under data uncertainty. For example, in operating room scheduling the decision maker must define appropriate limits for personnel overtime while accounting for random surgery durations. Typical approaches to hedge against...

We present relaxations for discrete optimization problems using approximate linear programs (ALPs) defined on multiple networks that represent different state-space aggregations. Our network ALP leverages information across these networks using a piecewise-constant value function approximation...