Minimizing Compositions of Differences-of-Convex Functions with Smooth Mappings
Hoai An Le Thi (),
Huynh Van Ngai () and
Tao Pham Dinh ()
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Hoai An Le Thi: Université de Lorraine, LGIPM, Département IA, F-57000 Metz, France; Institut Universitaire de France (IUF), 75000 Paris, France
Huynh Van Ngai: Department of Mathematics, University of Quynhon, Qui Nhon 590000, Vietnam
Tao Pham Dinh: Laboratory of Mathematics, INSA-Rouen, University of Normandie, 76801 Saint-Etienne-du-Rouvray Cedex, France
Mathematics of Operations Research, 2024, vol. 49, issue 2, 1140-1168
Abstract:
We address the so-called DC (difference-of-convex functions) composite minimization problems (or DC composite programs ) whose objective function is a composition of a DC function with a continuously differentiable mapping. We first develop an algorithm named DC composite algorithm (DCCA in short) for unconstrained DC composite programs and further extend to DC composite programs with constraints of inclusion associated with a smooth mapping and a closed convex set. The convergence analysis of the proposed algorithms is investigated. Applications of DCCA for two different problems, computation of the numerical radius of a square matrix and minimization of composite energies, are presented.
Keywords: Primary: 90C30; 49M37; secondary: 49J52; 90C26; 65K05; 90C25; DC program; DCA; DC composite function; DC composite algorithm; proximal regularization; subdifferential; penalization (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormoor:v:49:y:2024:i:2:p:1140-1168
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