Linear Programming Duality

Related lectures (32)

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

Introduces unweighted bipartite matching and its solution using linear programming and the simplex method.

Covers the concept of matroids, focusing on matroid intersection and the properties of subsets of a ground set.

Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.

Covers linear programming duality and complementary slackness condition.

Covers distributions, derivatives, convergence, and continuity criteria in function spaces.

Discusses the Ford-Fulkerson method and strongly connected components in graph algorithms.

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

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.