Stock-out Prediction in Multi-echelon Networks

no code implementations • 20 Sep 2017 • Afshin Oroojlooyjadid, Lawrence Snyder, Martin Takáč

In multi-echelon inventory systems the performance of a given node is affected by events that occur at many other nodes and in many other time periods.

A Deep Q-Network for the Beer Game: A Deep Reinforcement Learning algorithm to Solve Inventory Optimization Problems

no code implementations • 20 Aug 2017 • Afshin Oroojlooyjadid, MohammadReza Nazari, Lawrence Snyder, Martin Takáč

The game is a decentralized, multi-agent, cooperative problem that can be modeled as a serial supply chain network in which agents cooperatively attempt to minimize the total cost of the network even though each agent can only observe its own local information.

Management Transfer Learning

Applying Deep Learning to the Newsvendor Problem

2 code implementations • 7 Jul 2016 • Afshin Oroojlooyjadid, Lawrence Snyder, Martin Takáč

However, approximating the probability distribution is not easy and is prone to error; therefore, the resulting solution to the newsvendor problem may be not optimal.