Mixed symmetric duality in nondifferentiable mathematical programming

Xin Min Yang, Kok Lay Teo, Xiaoqi Yang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)

Abstract

A mixed symmetric dual formulation is presented for a class of nondifferentiable nonlinear programming problems with multiple arguments. Weak, strong and converse duality theorems are established. The mixed symmetric dual formulation unifies the two exsting symmetric dual formulations in the literature.
Original languageEnglish
Pages (from-to)805-815
Number of pages11
JournalIndian Journal of Pure and Applied Mathematics
Volume34
Issue number5
Publication statusPublished - 1 May 2003

Keywords

  • Generalized Convexity
  • Nondifferentiable Nonlinear Programming
  • Support Function
  • Symmetric Duality

ASJC Scopus subject areas

  • Mathematics(all)
  • Applied Mathematics

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