Optimization, Linear Programming, Convex Optimization, Duality, Towards Data Science.
as dual feasibility, states that x is also a feasible solution to the dual problem. λ and v are called the Lagrangian multipliers (or dual variables) corresponding to the constraints Ax ≥ b and x ≥ 0, respectively. Finally, condition (3) is called complementary slackness. Specifically, λ(Ax - b) =