more likely to occur and is greater in size in supply chains in which inventory control is centralized rather than …

likely to occur and is greater in size in supply chains in which inventory control is centralized rather than decentralized …

We apply Multi-Agent Deep Reinforcement Learning (MADRL) to inventory management problems with multiple echelons and …-Agent Proximal Policy Optimization (HAPPO) on the multi-echelon inventory management problems in both a serial supply chain and a … results also verify MADRL's potential in solving various multi-echelon inventory management problems with complex supply chain …

and infinite horizons. The theory is illustrated by using Cobb-Douglas demand functions as the deterministic part, while a … random variable brings in stochasticity into the model. Because our theory is very flexible with respect to the assumptions …

We consider a multi-period Newsvendor problem where the seller decides the initial inventory level and dynamically sets … not Markovian. The stochastic control formulation of this problem is intractable since the inventory dynamics depend on …. We demonstrate that, in general, ignoring product returns in inventory planning and pricing decisions results in a 20 …

"Inventory Analytics provides a comprehensive and accessible introduction to the theory and practice of inventory … control – a significant research area central to supply chain planning. The book outlines the foundations of inventory systems … and surveys prescriptive analytics models for deterministic inventory control. It further discusses predictive analytics …

We propose inventory replenishment and lateral transshipment policies for a distribution network. The distribution … satisfied demands and lateral transshipment, back order and lost sale costs for unsatisfied demands, and inventory holding costs …