Constraint qualifications in convex vector semi-infinite optimization

M.A. Goberna, F. Guerra-Vazquez and M.I. Todorov

European Journal of Operational Research, 2016, vol. 249, issue 1, 32-40

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.

Keywords: Multiobjective optimization; Convex optimization; Semi-infinite optimization; Constraint qualifications (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:249:y:2016:i:1:p:32-40

DOI: 10.1016/j.ejor.2015.08.062

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