Linear programming relaxation

Related lectures (32)

Page 3 of 4

Explores convexifying nonconvex problems using SDP and SOCP relaxations in the context of optimal power flow.

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

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

Revisits network flows with capacities, focusing on bounded flow problems and different formulations to approach them.

Explores convexifying nonconvex problems through relaxation techniques, illustrated with total variation reconstruction examples.

Explores finding the initial Basic Feasible Solution (BFS) in a linear program.

Covers deriving basic linear program representation, finding solutions, and exploring optimality.

Covers MAE regression, convex hull, reformulation advantages, and practical problems with decision variables and constraints.

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

Covers the process of solving Linear Programs (LPs) using the simplex method.