Second order duality for nondifferentiable minimax programming problems with generalized convexity

Z. Husain; Anurag Jayswal; I. Ahmad

doi:10.1007/s10898-008-9360-4

Second order duality for nondifferentiable minimax programming problems with generalized convexity

Z. Husain^*
, Anurag Jayswal
, I. Ahmad

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

16 Scopus citations

Abstract

In this paper, we are concerned with a class of nondifferentiable minimax programming problem and its two types of second order dual models. Weak, strong and strict converse duality theorems from a view point of generalized convexity are established. Our study naturally unifies and extends some previously known results on minimax programming.

Original language	English
Pages (from-to)	593-608
Number of pages	16
Journal	Journal of Global Optimization
Volume	44
Issue number	4
DOIs	https://doi.org/10.1007/s10898-008-9360-4
State	Published - Aug 2009
Externally published	Yes

Bibliographical note

Funding Information:
Acknowledgements The research of Z. Husain is supported by the Department of Atomic Energy, Government of India, under the NBHM Post-Doctoral Fellowship Program No. 40/9/2005-R&D II/2398.

Keywords

Generalized convexity
Minimax programming
Nondifferentiable programming
Second order duality

ASJC Scopus subject areas

Computer Science Applications
Management Science and Operations Research
Control and Optimization
Applied Mathematics

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10.1007/s10898-008-9360-4

Cite this

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abstract = "In this paper, we are concerned with a class of nondifferentiable minimax programming problem and its two types of second order dual models. Weak, strong and strict converse duality theorems from a view point of generalized convexity are established. Our study naturally unifies and extends some previously known results on minimax programming.",

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author = "Z. Husain and Anurag Jayswal and I. Ahmad",

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N2 - In this paper, we are concerned with a class of nondifferentiable minimax programming problem and its two types of second order dual models. Weak, strong and strict converse duality theorems from a view point of generalized convexity are established. Our study naturally unifies and extends some previously known results on minimax programming.

AB - In this paper, we are concerned with a class of nondifferentiable minimax programming problem and its two types of second order dual models. Weak, strong and strict converse duality theorems from a view point of generalized convexity are established. Our study naturally unifies and extends some previously known results on minimax programming.

KW - Generalized convexity

KW - Minimax programming

KW - Nondifferentiable programming

KW - Second order duality

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Second order duality for nondifferentiable minimax programming problems with generalized convexity

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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