ISSN:
1436-4646
Keywords:
Duality
;
Lagrangian
;
Nonlinear Programming
;
Fractional Programming
;
Pseudoconvex Function
;
Sufficient Conditions for Optimality
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
,
Mathematics
Notes:
Abstract Pseudoconvexity of a function on one set with respect to some other set is defined and duality theorems are proved for nonlinear programming problems by assuming a certain kind of convexity property for a particular linear combination of functions involved in the problem rather than assuming the convexity property for the individual functions as is usually done. This approach generalizes some of the well-known duality theorems and gives some additional strict converse duality theorems which are not comparable with the earlier duality results of this type. Further it is shown that the duality theory for nonlinear fractional programming problems follows as a particular case of the results established here.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01593799
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