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A Smoothing Penalty Function Algorithm for Two-Cardinality Sparse Constrained Optimization Problems
被引:2
|作者:
Min, Jiang
[1
]
Meng, Zhiqing
[1
]
Zhou, Gengui
[1
]
Shen, Rui
[1
]
机构:
[1] Zhejiang Univ Technol, Coll Econ & Management, Hangzhou, Zhejiang, Peoples R China
来源:
2018 14TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS)
|
2018年
基金:
中国国家自然科学基金;
关键词:
Two-Cardinality sparse constrained optimization problems;
smoothing penalty function;
algorithm;
penalty parameter;
SIGNAL RECOVERY;
D O I:
10.1109/CIS2018.2018.00018
中图分类号:
TP31 [计算机软件];
学科分类号:
081202 ;
0835 ;
摘要:
In this paper, a smoothing penalty function for two-cardinality sparse constrained optimization problems is presented. The paper proves that this type of the smoothing penalty functions has good properties in helping to solve two-cardinality sparse constrained optimization problems. Moreover, based on the penalty function, an algorithm is presented to solve the two-cardinality sparse constrained optimization problems, with its convergence under some conditions proved. A numerical experiment shows that a satisfactory approximate optimal solution can be obtained by the proposed algorithm.
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页码:45 / 49
页数:5
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