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A New Class of Filled Functions for Global Minimization.

Authors :
Hao, Yue
Liu, Jiming
Wang, Yu-Ping
Cheung, Yiu-ming
Yin, Hujun
Jiao, Licheng
Ma, Jianfeng
Jiao, Yong-Chang
He, Xiaoliang
Xu, Chengxian
Zhu, Chuanchao
Source :
Computational Intelligence & Security; 2005, p1088-1093, 6p
Publication Year :
2005

Abstract

Filled function method is a type of efficient methods to solve global optimization problems arisen in non-convex programming. In this paper, a new class of filled functions is proposed. This class of filled functions has only one adjustable parameter a. Several examples of this class of filled functions with specified parameter values are given, which contain the filled functions proposed in [3] and [4]. These examples show this class of filled functions contains more simple functions, therefore this class of filled functions have better computability. An algorithm employing the proposed filled function is presented, and numerical experiments show that the proposed filled functions are efficient. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540308188
Database :
Supplemental Index
Journal :
Computational Intelligence & Security
Publication Type :
Book
Accession number :
32962258
Full Text :
https://doi.org/10.1007/11596448_162