A new filled function method with unconstrained global optimization

被引：0
|
作者：
Yang, Xiaolin [1 ]
Zhou, Bin [2 ]
Feng, Jun [1 ]
机构：
[1] Chengdu Univ Technol, Coll Management Sci, Chengdu, Sichuan, Peoples R China
[2] Southwest Petr Univ, Sch Sci, Chengdu, Sichuan, Peoples R China
来源：
2017 13TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS) | 2017年
基金：
中国国家自然科学基金;
关键词：
filled function method; parameter; deterministic; global optimization; ONE-PARAMETER; MINIMIZERS;
D O I：
10.1109/CIS.2017.00119
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we construct a new filled function method, which is continuously differentiable and including one parameter. The filled function is not sensitive to parameter, and the overflow is overcame. A new filled function algorithm is proposed. The numerical experiments show that the proposed filled function algorithm is efficient and effective.
引用
收藏
页码：512 / 515
页数：4
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