Part I of this three-part series described semiconductor supply chains from the decision-
making and functional perspectives, using this as a framework to review the industrial …

We develop the first approximation algorithms with worst-case performance guarantees for
periodic-review perishable inventory systems with general product lifetime, for both …

Motivated by service capacity-management problems in healthcare contexts, we consider a
multiresource allocation problem with two classes of jobs (elective and emergency) in a …

In this paper, we propose to use distributed model predictive control for supply chain
optimization. In particular, we focus on inventory management in supply chains. We use …

We consider two classical stochastic inventory control models, the periodic-review stochastic
inventory control problem and the stochastic lot-sizing problem. The goal is to coordinate a …

Lost sales inventory models with large lead times, which arise in many practical settings, are
notoriously difficult to optimize due to the curse of dimensionality. In this paper, we show that …

We study the classical multiperiod capacitated stochastic inventory control problems in a
data-driven setting. Instead of assuming full knowledge of the demand distributions, we …

Inventory models with lost sales and large lead times have traditionally been considered
intractable due to the curse of dimensionality. Recently, Goldberg and coauthors laid the …

In this paper, we describe the first computationally efficient policies for stochastic inventory
models with lost sales and replenishment lead times that admit worst-case performance …

Managing perishable inventory systems with positive lead times and finite ordering
capacities is important but notoriously difficult in both theory and computation. The optimal …