Abstract:
The gradient projection method and Newton’s method are extended to the case where the constraints are nonconvex and are represented by a smooth surface. Necessary extremum conditions and the convergence of the methods are examined.
Key words:
smooth surface, gradient projection method, Newton's method, projection on a nonconvex set, necessary condition for a local minimum, convergence of an algorithm.