Treffer: SADDLE POINTS CRITERIA VIA A SECOND ORDER η-APPROXIMATION APPROACH FOR NONLINEAR MATHEMATICAL PROGRAMMING INVOLVING SECOND ORDER INVEX FUNCTIONS

Title:
SADDLE POINTS CRITERIA VIA A SECOND ORDER η-APPROXIMATION APPROACH FOR NONLINEAR MATHEMATICAL PROGRAMMING INVOLVING SECOND ORDER INVEX FUNCTIONS
Authors:
Source:
Kybernetika. 47(2):222-240
Publisher Information:
Praha: Institute of Information Theory and Automation of the Academy of Sciences of the Czech Republic, 2011.
Publication Year:
2011
Physical Description:
print, 13 ref
Original Material:
INIST-CNRS
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Faculty of Mathematics and Computer Science, University of Łódź, Banacha 22, 90-238 Łódź, Poland
ISSN:
0023-5954
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Operational research. Management
Accession Number:
edscal.24321704
Database:
PASCAL Archive

Weitere Informationen

In this paper, by using the second order η-approximation method introduced by Antczak [3], new saddle point results are obtained for a nonlinear mathematical programming problem involving second order invex functions with respect to the same function η. Moreover, a second order η-saddle point and a second order η-Lagrange function are defined for the so-called second order η-approximated optimization problem constructed in this method. Then, the equivalence between an optimal solution in the original mathematical programming problem and a second order η-saddle point of the second order η-Lagrangian in the associated second order η-approximated optimization problem is established. Finally, some example of using this approach to characterize of solvability of some O.R. problem is given.