Constraint qualifications in convex vector semi-infinite optimization

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Title: Constraint qualifications in convex vector semi-infinite optimization
Authors: Goberna, Miguel A. | Guerra Vázquez, Francisco | Todorov, Maxim I.
Research Group/s: Laboratorio de Optimización (LOPT)
Center, Department or Service: Universidad de Alicante. Departamento de Matemáticas
Keywords: Multiobjective optimization | Convex optimization | Semi-infinite optimization | Constraint qualifications
Knowledge Area: Estadística e Investigación Operativa
Issue Date: 16-Feb-2016
Publisher: Elsevier
Citation: European Journal of Operational Research. 2016, 249(1): 32-40. doi:10.1016/j.ejor.2015.08.062
Abstract: Convex vector (or multi-objective) semi-infinite optimization deals with the simultaneous minimization of finitely many convex scalar functions subject to infinitely many convex constraints. This paper provides characterizations of the weakly efficient, efficient and properly efficient points in terms of cones involving the data and Karush–Kuhn–Tucker conditions. The latter characterizations rely on different local and global constraint qualifications. The results in this paper generalize those obtained by the same authors on linear vector semi-infinite optimization problems.
ISSN: 0377-2217 (Print) | 1872-6860 (Online)
DOI: 10.1016/j.ejor.2015.08.062
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS)
Peer Review: si
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Appears in Collections:INV - LOPT - Artículos de Revistas

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