On Mixed Symmetric Duality in Mathematical Programming

OPSEARCH ◽  
1999 ◽  
Vol 36 (2) ◽  
pp. 165-171 ◽  
Author(s):  
S. Chandra ◽  
I. Husain ◽  
Abha
Author(s):  
Izhar Ahmad ◽  
Divya Agarwal ◽  
Kumar Gupta

Duality theory plays an important role in optimization theory. It has been extensively used for many theoretical and computational problems in mathematical programming. In this paper duality results are established for first and second order Wolfe and Mond-Weir type symmetric dual programs over general polyhedral cones in complex spaces. Corresponding duality relations for nondifferentiable case are also stated. This work will also remove inconsistencies in the earlier work from the literature.


Author(s):  
C. H. Scott ◽  
T. R. Jefferson

AbstractRecently we have developed a completely symmetric duality theory for mathematical programming problems involving convex functionals. Here we set our theory within the framework of a Lagrangian formalism which is significantly different to the conventional Lagrangian. This allows various new characterizations of optimality.


2011 ◽  
Vol 2011 ◽  
pp. 1-14 ◽  
Author(s):  
Ravi P. Agarwal ◽  
Izhar Ahmad ◽  
S. K. Gupta ◽  
N. Kailey

This paper is concerned with a pair of second-order mixed symmetric dual programs involving nondifferentiable functions. Weak, strong, and converse duality theorems are proved for aforementioned pair using the notion of second-orderF-convexity/pseudoconvexity assumptions.


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