Teaching students supply chain risk using a linear programming model of the fictitious online retailer Elbe

Abstract

The fictitious online retailer Elbe faces a deterministic demand for products over a geographic area and fulfills this demand using supply nodes and fulfillment centers. Experiential learning using provided solver and ILOG models (available upon request from the authors) for this supply chain allows students to experiment with disturbances in the distribution network where facilities go offline as a result of, for example, natural disasters. Students are shown how mathematical models can be used to plan the flow of product in real-world settings, as well as how these models can be used to react to supply chain risk. These models can be used in advanced undergraduate- or graduate-level classes in supply chain and operations management, leaving students with an appreciation of the models and their usefulness in real-world applications, as well as an increased understanding of supply chain risk and its impact on demand fulfillment.

Keywords:

• Experiential learning
• mathematical programmingprograming
• supply chain risk
• transportation models