Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/12027
Title: Nonlinear augmented lagrangian for nonconvex multiobjective optimization
Authors: Chen, C
Cheng, TCE 
Li, S
Yang, X 
Keywords: Exact penalization
Multiobjective optimization
Nonlinear augmented lagrangian
Ordering cone
Set-Valued maps
Strong duality
Issue Date: 2011
Publisher: American Institute of Mathematical Sciences
Source: Journal of industrial and management optimization, 2011, v. 7, no. 1, p. 157-174 How to cite?
Journal: Journal of industrial and management optimization 
Abstract: In this paper, based on the ordering relations induced by a pointed, closed and convex cone with a nonempty interior, we propose a nonlinear augmented Lagrangian dual scheme for a nonconvex multiobjective optimization problem by applying a class of vector-valued nonlinear augmented Lagrangian penalty functions. We establish the weak and strong duality results, necessary and sufficient conditions for uniformly exact penalization and exact penalization in the framework of nonlinear augmented Lagrangian. Our results include several ones in the literature as special cases.
URI: http://hdl.handle.net/10397/12027
ISSN: 1547-5816
EISSN: 1553-166X
DOI: 10.3934/jimo.2011.7.157
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