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Registration:
See below.
Objectives:
This PhD course introduces quantitative models for inventory and planning decisions in supply chains under uncertainty. The course focuses on how demand uncertainty, service requirements, replenishment lead times, and planning updates affect inventory decisions across multiple items and supply-chain stages.
Course description:
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Program:
The first two days focus on multi-echelon inventory models, primarily based on Chapter 8 of Paul Zipkin’s Foundations of Inventory Management. These sessions introduce the modelling principles underlying the most fundamental multi-echelon supply chain structures, including serial, distribution, and assembly systems. In addition, they cover analytical models and optimization approaches for inventory decision-making in these systems, with a particular emphasis on determining optimal inventory policies across multiple echelons.
The third day introduces guaranteed service models, based on Chapter 6 of Snyder and Shen’s Fundamentals of Supply Chain Theory. The session discusses service-time decisions, net replenishment times, and safety-stock placement in multi-echelon supply chains. It also connects these models to rolling-horizon planning, forecast updating, planning nervousness, and the bullwhip effect, drawing on selected rolling-horizon papers.
The fourth day is devoted to student paper presentations, guided class discussion, and research-oriented reflection. Students work in pairs, with each pair assigned one paper to present and extend. Each presentation block includes a summary of the paper, a discussion of its modelling approach and main assumptions, a proposed forward-looking extension, discussant feedback from another group, and class discussion. The final part of the day is used for course synthesis and discussion of the written report. All students are expected to read the selected papers and prepare short discussion notes before the final day.
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