Optimization Models and Methods

IEORE4004 Optimization Models and Methods

Instructor: Shipra Agrawal

Fall and Spring 

3 pts. Lect: 3. Refer to course syllabus. This is a required course for graduate students in Management Science & Engineering, Industrial Engineering, and Operations Research.  This is also required for students in the Undergraduate Advanced Track. This class is an introduction to the fundamental methods used in deterministic operations research. Topics covered will include linear programming, network flows, dynamic programming, and nonlinear programming. While we shall discuss the underlying theory with some occasional proofs, the emphasis will be on modeling. Applications of these ideas in various settings will be discussed. Students will learn modeling skills, and develop the ability to build, analyze, and reason logically with models. They will also learn to design and analyze algorithms, and to distinguish good algorithms from not-so good ones. They will also appreciate the capabilities and limitations of deterministic models in operations research.