Linear Programming Duality

Related lectures (32)

Page 1 of 4

Covers optimization problems in path finding and portfolio allocation.

Covers linear programming duality and complementary slackness condition.

Explains the process of finding an initial Basic Feasible Solution for linear optimization problems using the Simplex Algorithm.

Explores the concept of duality in linear programming, discussing the relationship between primal and dual problems.

Covers the basics of linear optimization, including equations, polyhedrons, feasible directions, and optimal solutions.

Explores duality in linear programming, strong duality, complementary slackness, and the economic interpretation of dual variables as prices.

Covers sensitivity analysis in linear programming, focusing on optimal solutions and their sensitivities to changes.

Explores the formulation of the auxiliary problem in linear optimization and its role in optimal decision-making.

Covers weak and strong duality in optimization problems, focusing on Lagrange multipliers and KKT conditions.

Covers linear programming, weighted bipartite matching, and vertex cover problems in optimization.