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MATH 435 - Linear Optimization

Course Description: 

Introduction to both theoretical and algorithmic aspects of linear optimization: geometry of linear programs, simplex method, anticycling, duality theory and dual simplex method, sensitivity analysis, large scale optimization via Dantzig-Wolfe decomposition and Benders decomposition, interior point methods, network flow problems, integer programming. Credit may not be granted for both MATH 435 and MATH 535.

Credit: 

(3-0-3)

Prerequisite: 

[(MATH 332 with min. grade of D)]

Corequisite: 

None