This course provides a rigorous treatment of linear and integer optimization. It is designed for students who want to build large-scale optimization models and need an understanding of the underlying theory. The course will cover polyhedral theory, projection and inverse projection techniques for systems of linear inequalities, simplex and interior point algorithms, duality, decomposition techniques, and cutting planes. While this course is theoretical in nature, we will continually illustrate application of the theory to solving real, large-scale problems.

IMPORTANT: This class is open to all University of Chicago students. However, it is designed for Ph.D. students. The course is theoretical in nature. The vast majority of the assignments are theorem-proof oriented. This class is very much like an upper level math class.

First Class Assignment: Please email the instructor for the first class assignment.

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