Constraint qualifications in linear vector semi-infinite optimization

► We characterize different types of efficient points of linear VSIO problems. ► Characterizations in terms of cones involving the data and KKT conditions. ► Methodology based on identifying tangent cones at feasible points. ► Tangent cones only computable under (global or local) constraint qualific...

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Vydáno v:European journal of operational research Ročník 227; číslo 1; s. 12 - 21
Hlavní autoři: Goberna, M.A., Guerra-Vazquez, F., Todorov, M.I.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier B.V 16.05.2013
Elsevier
Elsevier Sequoia S.A
Témata:
Cone conditions
Constraint qualifications
KKT conditions
Linear vector semi-infinite optimization
Mathematical functions
Mathematical models
Multiple objective programming
Nonlinear programming
Optimization techniques
Qualifications
Studies
Cone conditions
KKT conditions
Constraint qualifications
Linear vector semi-infinite optimization
Multiple objective programming
ISSN:0377-2217, 1872-6860
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Shrnutí:► We characterize different types of efficient points of linear VSIO problems. ► Characterizations in terms of cones involving the data and KKT conditions. ► Methodology based on identifying tangent cones at feasible points. ► Tangent cones only computable under (global or local) constraint qualifications. Linear vector semi-infinite optimization deals with the simultaneous minimization of finitely many linear scalar functions subject to infinitely many linear constraints. This paper provides characterizations of the weakly efficient, efficient, properly efficient and strongly 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 global constraint qualifications are illustrated on a collection of selected applications.
Bibliografie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2012.09.006