A NEW PARAMETER-FREE FILLED FUNCTION METHOD FOR GLOBAL OPTIMIZATION

被引：0
|
作者：
Yang, Lili [1 ]
Gao, Yuelin [2 ]
Li, Jia [1 ]
机构：
[1] North Minzu Univ, Sch Math & Informat Sci, Yinchuan 750021, Peoples R China
[2] North Minzu Univ, Ningxia Prov Cooperat Innovat Ctr Sci Comp & Intel, Sch Math & Informat Sci, Yinchuan 750021, Peoples R China
来源：
JOURNAL OF NONLINEAR AND CONVEX ANALYSIS | 2024年 / 25卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Filled function; global optimization; parameter-free; global minimizer; MINIMIZER;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, a noval parameter -free filled function is proposed based on existing filled functions and their limitations. Firstly, the filling properties are analyzed. Secondly, the corresponding filled function algorithm is designed by integrating the proposed filled function and quasi-Newton method. Finally, 9 commonly used benchmark functions are tested. The experimental results show that the proposed filled function has good performance and can successfully escape from the current local minima. Compared with existing algorithms, the effectiveness and practicality of this algorithm are demonstrated.
引用
收藏
页码：475 / 487
页数：13
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