An algorithm for nonconvex lower semicontinuous optimization problems

In this paper we study an algorithm to find critical points of a lower semicontinuous nonconvex function. We use the Moreau regularization for a special type of functions belonging to the class of prox-regular functions which have very interesting algorithmic properties. We show that it is possible...

Descripción completa

Autor Principal: Cornejo Zúñiga, Oscar
Formato: Artículo
Idioma: English
Publicado: Algorithmic Applications in Management 2015
Materias:
Acceso en línea: 9783540324409
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Sumario: In this paper we study an algorithm to find critical points of a lower semicontinuous nonconvex function. We use the Moreau regularization for a special type of functions belonging to the class of prox-regular functions which have very interesting algorithmic properties. We show that it is possible to generate an algorithm in order to obtain a critical point using the theory developed for the composite functions and also the results for the solutions of nonsmooth vectorial equations. We prove the convergence of the algorithm and some estimations of the convergence speed.