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.
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