Overview
Description
Theoretical optimization theory; linear programming, simplex method convexity, duality theory, integer and fractional programming algorithms, Kuhn-Tucker theory, linear complementary problem, Lemke’s algorithm.
Units
Lecture3
Catalog Details
Offering
Offered: Every Fall - Even Years
Terms
fall
Attributes
Standard
Learning Outcomes
- demonstrate understanding of and facility with all of the mathematical details of the simplex algorithm for solving linear programs, duality theory, and a linear algebraic approach to sensitivity analysis for linear programs, including being able to formally prove results in these areas.
- demonstrate understanding of and facility with extensions of the simplex algorithm to solve nonlinear problems, such as integer programming, fractional programming, and linear complementarity problems.
- demonstrate understanding of the Kuhn Tucker conditions for nonlinear programming, how they are related to optimality conditions for certain optimization problems, and how to use them to solve certain convex and non-convex problems.