Course Page

Linear Programming

Course Number:

47834


Faculty

John Hooker, jh38@andrew.cmu.edu


Program

PHD


Concentrations

Operations Research or Statistics


Course Description

Linear programming lies at the basis of modern optimization theory. This course focuses primarily on linear programming theory and algorithms, leaving beyond the scope of its practical applications. The main topics to be covered include modeling examples and expressive power of linear programs, polyhedral sets and their geometry, theory of systems of linear inequalities and duality, classical linear optimization algorithms (simplex and network simplex), and decomposition approaches for large-scale optimization. If time permits polynomial time solvability of linear programs, extensions to conic optimization problems, conic duality, and an introduction to interior point methods are topics of interest in the given order.

Format

Lecture: 100min/wk and Recitation: 50min/wk


Pre-requisites

None