A proximal point algorithm for DC fuctions on Hadamard manifolds

J. Souza () and P. Oliveira ()

Journal of Global Optimization, 2015, vol. 63, issue 4, 797-810

Abstract: An extension of a proximal point algorithm for difference of two convex functions is presented in the context of Riemannian manifolds of nonposite sectional curvature. If the sequence generated by our algorithm is bounded it is proved that every cluster point is a critical point of the function (not necessarily convex) under consideration, even if minimizations are performed inexactly at each iteration. Application in maximization problems with constraints, within the framework of Hadamard manifolds is presented. Copyright Springer Science+Business Media New York 2015

Keywords: Nonconvex optimization; Proximal point algorithm; DC functions; Hadamard manifolds; 49M30; 90C26; 90C48 (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s10898-015-0282-7

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