INSE6300 Supply Chain Management (Fall 2018)
Instructor: Jia Yuan Yu.
Lectures: Fridays, 17:45--20:15, room FG B050.
Office hours: Fridays, 15:45--17:45 in room EV7.635.
Course description: The course is a continuation of Supply Chain Design. We focus on quality-of-service and performance guarantees in the context of data-driven decision-making problems in supply chains.
Understanding Machine Learning, S. Shalev-Shwartz, S. Ben-David.
Markov Decision Processes, Martin Puterman.
Theory of Point Estimation, E. L. Lehmann and G. Casella.
Fundamentals of Supply Chain Theory, Lawrence V. Snyder, Zuo-Jun Max Shen.
Exploratory Data Analysis, H. Seltman, [PDF].
50 years of Data Science, D. Donoho, [PDF].
Game Theory in Supply Chain Analysis, G. P. Cachon, S. Netessine, [PDF].
- Lecture 0: Intro [PDF].
- Lecture 1: Data [PDF].
- Lecture 2: Control charts [PDF].
- Lecture 3: Inventory management [PDF].
- Lecture 4: Dynamic programming [PDF] (long version: [PDF]).
- Lecture 5: Parametric estimation [PDF].
- Lecture 6: Hypothesis testing [PDF].
- Lecture 7: Queueing [PDF].
- Lecture 8: Gittins index [PDF].
- Lecture 9: Cooperative game theory [PDF].
- Assignment 1: Control charts [PDF].
- Assignment 2: Strategic decision making [PDF].
Describe an application of supply chain methods to solve a new problem (e.g., using dataset found on the Internet, from open-data initiatives, government agencies, etc.). Here, you will motivate the problem, model it, propose a solution approach, and analyse this solution.
You will have to produce a concise report (neither too short nor too long), and give a presentation on it.