Groups
Interior point methods solve constrained optimization by replacing hard constraints with a smooth barrier that becomes infinite at the boundary, keeping iterates strictly inside the feasible region.
A convex optimization problem minimizes a convex function over a convex set, guaranteeing that every local minimum is a global minimum.