In stochastic versions of combinatorial optimization problems, the goal is to optimize an objective function under constraints that specify the feasible solutions, when some parameters involve uncertainty. We focus on maximizing a linear objective ∑N i=1Wixi, where x1, . . . , xN are the decision variables, W1, . . . ,WN are mutually independent random coefficients, and the constraints are dete...

This paper studies a model of community-based health care delivery for chronic diseases in a non-profit setting. In this setting, patients periodically access the health care delivery system, which influences their disease progression and consequently their health outcomes. We investigate how the provider can maximize community-level health outcomes through better operational decisions pertaini...

A make-to-order environment requires flexibility in the supply chain to facilitate fast response. Timely supply deliveries can be achieved in a cost-effective manner by having a portfolio of suppliers, or a portfolio of contracts with a single supplier, with different lead times and associated costs. In this paper we address the inventory management of such a system and evaluate the savings ass...

We study a finite-horizon lost-sales inventory model. The demand distribution is unknown and is dynamically updated based on the previous sales data in a Bayesian fashion. We derive a samplepath representation of the first order optimality condition, which characterizes the key tradeoff of the problem. The expression allows us to see why the computation of the optimal policy is difficult and wh...

Optimizing resource allocation in interdependent security problems is a serious challenge for homeland security. In this article, we present the equilibrium strategies for multiple interdependent defenders in a model where threats occur over time. We show that the existence of myopic agents can make it undesirable for non-myopic agents to invest in security when it would otherwise be in their i...

It is shown that stability of the celebrated MaxWeight or back pressure policies is a consequence of the following interpretation: either policy is myopic with respect to a surrogate value function of a very special form, in which the “marginal disutility” at a buffer vanishes for vanishingly small buffer population. This observation motivates the h-MaxWeight policy, defined for a wide class of...

To trade off tracking accuracy and interception risk in a multi-sensor multi-target tracking context, we study the sensor-scheduling problem where we aim to assign sensors to observe targets over time. Our problem is formulated as a partially observable Markov decision process, and this formulation is applied to develop a non-myopic sensor-scheduling scheme. We resort to extended Kalman filteri...

A general discrete-time stochastic control model is developed which encompasses many wellknown economic models. In the context of the general model, sufficient conditions are derived for the equivalence and approximate equivalence of myopic (sequential single-period) and global (simultaneous multi-period) expected return maximization. A bound provided for the global return loss resulting from m...

This paper reviews a number of recent contributions that study pension design with myopic individuals. Its objective is to explore how the presence of more or less myopic individuals affects pension design when individuals differ also in productivity. This double heterogeneity gives rise to an interesting interplay between paternalistic and redistributive considerations, which is at the heart o...