Course: Stochastics Models of Supply Chain Operations

Professor: Joachim Arts

ECTS: 2

Aims:

This course introduces students to advanced stochastic models and computational techniques in operations research/applied probability. We will especially study how these models and techniques are applied in supply chain management. These techniques are essential to our understanding of the role of uncertainty in many supply chain operations. We will give special attention to demand uncertainty and to the role of finite capacity in production systems with uncertain arrivals and processing times.

Objectives:

The student who followed this course

• Can use decomposition results to analyse supply chains with many stages
  (ClarkScarf and Rosling decomposition, nested newsvendor characterization of optimal policies).
• Can use Phase-type distributions to computationally analyse multi-echelon inventory systems.
• Can apply mean value analysis and generating functions to analyse simple queueing situations.
• Can use insensitive systems to models various common mechanism such as transportation systems and base-stock inventory policies.
• Knows the renewal reward theorem and how to apply it.
• Understands basic notions of asymptotic optimality.