Explores strong duality, complementary slackness, economic interpretation, and stochastic problem scenarios in linear programming.
Covers the KKT conditions and convex optimization, discussing constraint qualifications and tangent cones of convex sets.
Introduces linear programming basics, including optimization problems, cost functions, simplex algorithm, geometry of linear programs, extreme points, and degeneracy.
Explores duality in linear programming, strong duality, complementary slackness, and the economic interpretation of dual variables as prices.
Covers weak and strong duality in optimization problems, focusing on Lagrange multipliers and KKT conditions.
