Syllabus

Course Meeting Times

Lectures: 2 session / week, 1.5 hours / session

Course Objectives

The course will consider optimization models for supporting the following issues:

• Distribution Systems Planning
• Facility Sizing and Capacity Expansion
• Inventory Planning
• Network Design
• Production Planning and Scheduling
• Project Scheduling
• Supply Chain Management
• Portfolio Optimization
• Pricing
• Yield Management and Revenue Optimization

Course Organization

The course uses a combination of lectures, case discussions, selected readings, an accompanying textbook, hands-on projects and optimization challenges. It introduces some personal and industrial strength software packages, particularly the EXCEL spreadsheet package with its optimization provisions (its solver module) and the AMPL/CPLEX system for modeling and optimization.

Text

The texts Decision Modeling with Microsoft Excel, Sixth Edition by Moore, Weatherford, Eppen, Gould and Schmidt, Prentice Hall and AMPL A Modeling Language For Mathematical Programming by Fourer, Gay, Kernighan, Boyd & Fraser, are useful references both for the course material and the modeling tools we will rely on. We will provide additional material as the course progresses.

Course Project

This course involves a group project that provides us with an opportunity to consider topics that might not otherwise be covered in the course and to tailor the course offerings for your own interests. It also provides an opportunity for you to dig deeper into areas of special interest. You will work on this project with a team of four or five. Each team must consist of both on-campus and off-campus members. The general intent of your project is to teach yourself and the rest of us about some aspect of optimization. Potential topics include: existing optimization applications special to your company or industry, opportunities for optimization in your company or industry, special optimization tools or methodologies your company or industry uses or is considering, etc.

Grading

Grading will be based on several challenges, two exams and the team-based project: