Generalized α-invexity and nondifferentiable minimax fractional programming

S. K. Mishra, R. P. Pant, J. S. Rautela

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

In this paper, we study a nondifferentiable minimax fractional programming problem under the assumptions of α-invex function. In this paper we utilize the concept of α-invexity [M.A. Noor, On generalized preinvex functions and monotonicities, J. Inequalities Pure Appl. Math. 5 (2004) 1-9] and pseudo-α-invexity [S.K. Mishra, M.A. Noor, On vector variational-like inequality problems, J. Math. Anal. Appl. 311 (2005) 69-75]. We also introduce the concept of strict pseudo-α-invex and quasi-α-invex functions. We derive Karush-Kuhn-Tucker-type sufficient optimality conditions and establish weak, strong and converse duality theorems for the problem and its three different dual problems. The results in this paper extend several known results in the literature.

Original languageEnglish
Pages (from-to)122-135
Number of pages14
JournalJournal of Computational and Applied Mathematics
Volume206
Issue number1
DOIs
Publication statusPublished - 1 Sept 2007
Externally publishedYes

Keywords

  • Duality
  • Generalized convexity
  • Nondifferentiable minimax fractional programming problems
  • Sufficient optimality conditions
  • α-invexity

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics

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