An interior proximal linearized method for DC programming based on Bregman distance or second-order homogeneous kernels |
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Authors: | J X Cruz Neto P S M Santos J C O Souza |
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Institution: | 1. Department of Mathematics, Federal University of Piauí
, Teresina, Brazil.;2. CMRV, Federal University of Piauí
, Parnaíba, Brazil. https://orcid.org/0000-0002-1327-8779 |
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Abstract: | AbstractWe present an interior proximal method for solving constrained nonconvex optimization problems where the objective function is given by the difference of two convex function (DC function). To this end, we consider a linearized proximal method with a proximal distance as regularization. Convergence analysis of particular choices of the proximal distance as second-order homogeneous proximal distances and Bregman distances are considered. Finally, some academic numerical results are presented for a constrained DC problem and generalized Fermat–Weber location problems. |
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Keywords: | Interior proximal methods DC functions proximal distance Bregman distances second-order homogeneous kernels |
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