Linear Programming Basics

Related lectures (32)

Page 1 of 4

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

Covers the application of the two-phase Simplex algorithm to solve linear programming problems.

Explains network flows, LP formulations, simplex method, duality, and practical applications.

Explores Linear Programming Duality, covering weak duality, strong duality, Lagrange multipliers interpretation, and optimization constraints.

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

Explores certificates, proving solution existence, constraints, and linear programming duality.

Covers optimization problems in path finding and portfolio allocation.

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

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

Introduces the Simplex algorithm for solving flow problems and handling negative cost cycles.