Lagrange Duality for Evenly Convex Optimization Problems

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Title: Lagrange Duality for Evenly Convex Optimization Problems
Authors: Fajardo, Maria Dolores | Rodríguez Álvarez, Margarita | Vidal, José
Research Group/s: Laboratorio de Optimización (LOPT)
Center, Department or Service: Universidad de Alicante. Departamento de Matemáticas
Keywords: Evenly convex function | Generalized convex conjugation | Lagrange dual problem
Knowledge Area: Estadística e Investigación Operativa
Issue Date: Jan-2016
Publisher: Springer Science+Business Media New York
Citation: Journal of Optimization Theory and Applications. 2016, 168(1): 109-128. doi:10.1007/s10957-015-0775-z
Abstract: An evenly convex function on a locally convex space is an extended real-valued function, whose epigraph is the intersection of a family of open halfspaces. In this paper, we consider an infinite-dimensional optimization problem, for which both objective function and constraints are evenly convex, and we recover the classical Lagrange dual problem for it, via perturbational approach. The aim of the paper was to establish regularity conditions for strong duality between both problems, formulated in terms of even convexity.
Sponsor: This research was partially supported by MINECO of Spain, Grant MTM2011-29064-C03-02 and by Consellería d’Educació de la Generalitat Valenciana, Spain, Pre-doc Program Vali+d, DOCV 6791/07.06.2012 Grant ACIF-2013-156.
URI: http://hdl.handle.net/10045/62189
ISSN: 0022-3239 (Print) | 1573-2878 (Online)
DOI: 10.1007/s10957-015-0775-z
Language: eng
Type: info:eu-repo/semantics/article
Rights: © Springer Science+Business Media New York 2015. The final publication is available at Springer via http://dx.doi.org/10.1007/s10957-015-0775-z
Peer Review: si
Publisher version: http://dx.doi.org/10.1007/s10957-015-0775-z
Appears in Collections:INV - LOPT - Artículos de Revistas

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