Linear programming

Related lectures (32)

Page 3 of 4

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

Explores strong duality, complementary slackness, economic interpretation, and stochastic problem scenarios in linear programming.

Explores integer programming, John's Theorem, and the reduction to shortest vector computations in convex bodies.

Covers the optimization of a juice bottling process to reduce costs and enhance integration through non-linear programming.

Explains the Branch and Bound algorithm for heuristic maximization problems using LP relaxations and pruning techniques.

Explores relations between events, disjunctive constraints, and modeling with binary variables in optimization problems.

Covers the concept of linear optimization and the duality relationship between primal and dual problems.

Covers linear programming duality and complementary slackness condition.

Covers the basics of linear programming and the simplex method, focusing on finding optimal solutions and handling degeneracy.

Covers convex optimization problems, transformation to standard form, and optimality criteria for differentiable objectives.