Mixed-Type Duality on Nonsmooth Minimax Fractional Programming Involving Exponential (p, r)-Invexity

Considering a nonsmooth minimax fractional programming problem involving exponential (p, r)-invexity, we construct a mixed-type dual problem, which is performed by an incomplete Lagrangian dual model. This mixed-type dual model involves the Wolfe type dual and Mond-Weir type dual as the special case...

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Bibliographic Details
Published inNumerical functional analysis and optimization Vol. 35; no. 12; pp. 1560 - 1578
Main Authors Ho, Shun-Chin, Lai, Hang-Chin
Format Journal Article
LanguageEnglish
Published Taylor & Francis Group 02.12.2014
Subjects
Duality
Exponential type (p
Generalized subdifferential
Lipschitz function
Minimax fractional programming
r)-invex function
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Summary:Considering a nonsmooth minimax fractional programming problem involving exponential (p, r)-invexity, we construct a mixed-type dual problem, which is performed by an incomplete Lagrangian dual model. This mixed-type dual model involves the Wolfe type dual and Mond-Weir type dual as the special cases under exponential (p, r)-invexity. We establish the mixed-type duality problem with conditions for exponential (p, r)-invexity and prove that the optimal values of the primary problem and the mixed-type duality problem have no duality gap under the framwork of exponential (p, r)-invexity.
ISSN:0163-0563
1532-2467
DOI:10.1080/01630563.2014.895754