This paper constructs a model of a supply chain to examine how demand volatility is passed upstream through the chain. In particular, we seek to determine how likely it is that the chain experiences a bullwhip effect, where the variance of the upstream firm's production exceeds the variance of...

This paper constructs a model of a supply chain to examine how demand volatility is passed upstream through the chain. In particular, we seek to determine how likely it is that the chain experiences a bullwhip effect, where the variance of the upstream firms’ production exceeds the variance of...

We apply Multi-Agent Deep Reinforcement Learning (MADRL) to inventory management problems with multiple echelons and evaluate MADRL's performance to minimize the overall costs of a supply chain. We also examine whether the upfront-only information-sharing mechanism used in MADRL helps alleviate...

In this paper we derive useful sufficiency optimality conditions for a class of optimal control problems subject to differential inclusions and involving non-differentiable functions. A production inventory problem is solved to illustrate our results

This paper introduces recent developments in the analysis of inventory systems with partial observations. The states of these systems are typically conditional distributions, which evolve in infinite dimensional spaces over time. Our analysis involves introducing unnormalized probabilities to...

Firms adjust to differences in market size and demand uncertainty by changing the frequency and size of their export shipments. In our inventory model, transportation costs and optimal shipment frequency are determined on the basis of demand as well as inventory and per shipments costs. Using a...