Stochastic optimization methods for supply chains with perishable products

This book deals with inventory systems in supply chains that face risks that could render products unsalable. These risks include possible cooling system failures, transportation risks, packaging errors, handling errors, or natural quality deterioration over time like spoilage of food or blood products. Classical supply chain inventory models do not regard these risks. This thesis introduces novel cost models that consider these risks. It also analyzes how real-time tracking with RFID sensors and smart containers can contribute to decision making. To solve these cost models, this work presents new solution methods based on dynamic programming. In extensive computational studies both with experimental as well as real-life data from large players in the retailer industry, the solution methods prove to lead to substantially lower costs than existing solution methods and heuristics.