This course is designed to teach PhD students the methods and theory needed to do academic research in supply chain management. Supply chains are networks of organizations that supply and transform materials and distribute final products to consumers. Their efficient performance is critical to firm success. Supply chains aim to get the right product to the right place at the right time in the right quantity; in effect functioning as the “how” of matching supply and demand. Managing product, information, and financial flows to achieve these goals is challenging due to both the complexity of the decisions involved, and the dynamic unfolding of uncertainty. We will address these issues with rigorous analysis to identify effective strategies to manage relevant flows in the supply chain. Key topics covered include inventory management, facility location, and fulfillment.
The course will focus on mathematical models of a variety supply chain settings covering a range of demand, supply, and cost characteristics. Given a specific model, the main question we will address is how to design a policy to optimize the supply chain’s performance; i.e., a set of rules or parameters that govern decisions made in a changing supply chain context to improve some objective measure of performance. Our development of optimal policies will focus on rigorous mathematical proofs applicable to robust and general settings. To achieve this goal, the course will draw upon and assume some familiarity with optimization theory (dynamic, stochastic, linear, and integer programming), real analysis, measure theory, and statistics; and will introduce necessary concepts along the way.