Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/11481
Title: Duality and exact penalization for vector optimization via augmented Lagrangian
Authors: Huang, XX
Yang, XQ 
Keywords: Augmented lagrangian
Duality
Exact penalization, nonlinear lagrangian
Vector optimization
Issue Date: 2001
Publisher: Springer
Source: Journal of optimization theory and applications, 2001, v. 111, no. 3, p. 615-640 How to cite?
Journal: Journal of optimization theory and applications 
Abstract: In this paper, we introduce an augmented Lagrangian function for a multiobjective optimization problem with an extended vector-valued function. On the basis of this augmented Lagrangian, set-valued dual maps and dual optimization problems are constructed. Weak and strong duality results are obtained. Necessary and sufficient conditions for uniformly exact penalization and exact penalization are established. Finally, comparisons of saddle-point properties are made between a class of augmented Lagrangian functions and nonlinear Lagrangian functions for a constrained multiobjective optimization problem.
URI: http://hdl.handle.net/10397/11481
ISSN: 0022-3239
EISSN: 1573-2878
DOI: 10.1023/A:1012654128753
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