Augmented Lagrangian functions for constrained optimization problems

被引:0
|
作者
Y. Y. Zhou
X. Q. Yang
机构
[1] Soochow University,Department of Mathematics
[2] The Hong Kong Polytechnic University,Department of Applied Mathematics
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关键词
Constrained optimization problem; Augmented Lagrangian function; Coercive; Asymptotically minimizing sequence;
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学科分类号
摘要
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.
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页码:95 / 108
页数:13
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