Syllabus

This subject is a survey of analytic tools, approaches, and techniques which are useful in the design and operation of logistics systems and integrated supply chains. The material is taught from a managerial perspective, with an emphasis on where and how specific tools can be used to improve the overall performance and reduce the total cost of a supply chain. We place a strong emphasis on the development and use of fundamental models to illustrate the underlying concepts involved in both intra- and inter-company logistics operations.

Topics to be covered include:

• Demand Forecasting Tools
• Inventory Control Algorithms
• Transportation Operations and Management
• Vehicle Routing, Scheduling, and Fleet Dispatching Algorithms and Approaches
• Optimization of Transportation Carrier Operations
• Supply Chain Network Design
• Procurement, Sourcing, and Auctions (to include Combinatorial Auctions)
• Management and Minimization of Supply Chain Uncertainty
• Supply Contracts and Collaboration

In addition to model development, we will use examples from industry to provide illustrations of the concepts in practice. This is not, however, a case study course.

Course Objectives

The four primary objectives of this course are:

1. Introduce students to the analytic model based approach for analyzing logistics problems,
2. Reinforce the importance of using total supply chain costs in all analysis,
3. Provide students with techniques for measuring and managing supply chain uncertainty, and
4. Introduce the idea of using a portfolio of solutions, rather than a single approach, for real-world logistics problems.

Teaching Note

This subject is taught in a lecture/discussion format. There is no assigned textbook; all presentation graphics and instructor's lecture notes, as well as required and supplemental readings, are made available prior to class. Note also that the class will begin promptly at 8:00 AM.

Prerequisites

Permission of instructors. The course also presumes a basic understanding of calculus, probability and statistics, linear algebra, linear programming, micro-economics, and spreadsheets.

Instructors

Dr. Chris Caplice
Prof. Yossi Sheffi

Course Requirements and Grading Weights

Academic Honesty

All problem sets are individual, independent student assignments. While library research and the use of reference materials are permitted and encouraged, no collaboration among students is allowed. If you are unclear about any aspect of this policy, please ask one of the instructors for clarification.