Necessary optimality conditions for minimax programming problems with mathematical constraints

In this paper, necessary optimality conditions in terms of upper and/or lower subdifferentials of both cost and constraint functions are derived for minimax optimization problems with inequality, equality and geometric constraints in the setting of non-differentiatiable and non-Lipschitz functions i...

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Veröffentlicht in:Optimization Jg. 66; H. 11; S. 1755 - 1776
Hauptverfasser: Bao, Truong Q., Gupta, Pankaj, Khanh, Phan Q.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Philadelphia Taylor & Francis 02.11.2017
Taylor & Francis LLC
Schlagworte:
Economic models
Functions (mathematics)
fuzzy necessary optimality conditions
Geometric constraints
lower subdifferential necessary optimality conditions
Mathematical programming
minimax fractional programming
Minimax programming
Minimax technique
Nonlinear programming
upper subdifferential necessary optimality conditions
ISSN:0233-1934, 1029-4945
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Zusammenfassung:In this paper, necessary optimality conditions in terms of upper and/or lower subdifferentials of both cost and constraint functions are derived for minimax optimization problems with inequality, equality and geometric constraints in the setting of non-differentiatiable and non-Lipschitz functions in Asplund spaces. Necessary optimality conditions in the fuzzy form are also presented. An application of the fuzzy necessary optimality condition is shown by considering minimax fractional programming problem.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:0233-1934
1029-4945
DOI:10.1080/02331934.2017.1344238