Second-order sequence-based necessary optimality conditions in constrained nonsmooth vector optimization and applications

Second-order sequence-based necessary optimality conditions in constrained nonsmooth vector optimization and applications

Several notions of sequential directional derivatives and sequential local approximations are introduced. Under (first-order) Hadamard differentiability assumptions of the data at the point of study, these concepts are utilized to analyze second-order necessary optimality conditions, which rely on g...

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Veröffentlicht in:Positivity : an international journal devoted to the theory and applications of positivity in analysis 2018-03, Vol.22 (1), p.159-190
1. Verfasser: Tuan, Nguyen Dinh
Format: Artikel
Sprache:eng
Schlagworte:
Calculus of Variations and Optimal Control
Optimization
Econometrics
Fourier Analysis
Mathematics
Mathematics and Statistics
Minimax technique
Nonlinear programming
Operator Theory
Optimization
Potential Theory
Sequences
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Beschreibung
Zusammenfassung:Several notions of sequential directional derivatives and sequential local approximations are introduced. Under (first-order) Hadamard differentiability assumptions of the data at the point of study, these concepts are utilized to analyze second-order necessary optimality conditions, which rely on given sequences, for local weak solutions in nonsmooth vector optimization problems with constraints. Some applications to minimax programming problems are also derived.
ISSN:1385-1292
1572-9281
DOI:10.1007/s11117-017-0505-x