Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/22486
Title: Augmented Lagrangian functions for constrained optimization problems
Authors: Zhou, YY
Yang, XQ 
Keywords: Asymptotically minimizing sequence
Augmented Lagrangian function
Coercive
Constrained optimization problem
Issue Date: 2012
Publisher: Springer
Source: Journal of global optimization, 2012, v. 52, no. 1, p. 95-108 How to cite?
Journal: Journal of global optimization 
Abstract: In this paper, in order to obtain some existence results about solutions of the augmented Lagrangian problem for a constrained problem in which the objective function and constraint functions are noncoercive, we construct a new augmented Lagrangian function by using an auxiliary function. We establish a zero duality gap result and a sufficient condition of an exact penalization representation for the constrained problem without the coercive or level-bounded assumption on the objective function and constraint functions. By assuming that the sequence of multipliers is bounded, we obtain the existence of a global minimum and an asymptotically minimizing sequence for the constrained optimization problem.
URI: http://hdl.handle.net/10397/22486
ISSN: 0925-5001
EISSN: 1573-2916
DOI: 10.1007/s10898-011-9688-z
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