Intelligent bionic genetic algorithm (IB-GA) and its convergence
Intelligent bionic genetic algorithm (IB-GA) and its convergence
复制标题
智能仿生遗传算法(IB-GA)及其收敛性
DOI:
10.1016/j.eswa.2011.01.091
复制
发表时间:
2011-07
影响因子:
8.5
通讯作者:
Fachao Li, Li Da Xu, Chenxia Jin, Hong Wang
中科院分区:
文献类型:
--
作者:
Fachao Li, Li Da Xu, Chenxia Jin, Hong Wang
As a new kind of intelligence optimization method, genetic algorithms, with the features of simple structure and strong adaptability, achieves great success in many real applications. However, it has many shortcomings such as a greater computation complexity and more chance of being trapped in local states. In this paper, through analyzing the deficiency of the existing genetic operation and the essential characteristics of creature evolution from the angle of improving evolution efficiency, we propose a compound mutation strategy based on mutation criteria function, a multi-reserved strategy based on intelligence evolution, and a weak arithmetic crossover strategy reflecting different evolution modes. Furthermore, we establish an intelligent bionic genetic algorithm with structural features (denoted by IB-GA, for short). Finally, we analyze the performances of IB-GA with the theory of Markov chains and simulation technology. The results indicate that IB-GA is essentially an extension of ordinary GA and obviously better than ordinary GA in terms of computation efficiency and convergence performance.
登录
查看更多内容
DOI:
10.1017/cbo9781139626514
发表时间:
2014-02
期刊:
--
影响因子:
--
作者:
R. Gallager
通讯作者:
R. Gallager
DOI:
10.1016/b978-1-903996-55-3.x5008-7
发表时间:
2004
期刊:
--
影响因子:
--
作者:
Ken-iti Sato;O. Barndorff-Nielsen;Kiyosi Itô
通讯作者:
Ken-iti Sato;O. Barndorff-Nielsen;Kiyosi Itô
DOI:
10.2307/2291619
发表时间:
1982-12
期刊:
--
影响因子:
--
作者:
Sheldon M. Ross
通讯作者:
Sheldon M. Ross
DOI:
10.1016/s0169-7439(99)00057-x
发表时间:
2000-01
影响因子:
3.9
作者:
L. Balland;L. Estel;J. Cosmao;N. Mouhab
通讯作者:
L. Balland;L. Estel;J. Cosmao;N. Mouhab
DOI:
10.2307/1266103
发表时间:
1980-06
期刊:
--
影响因子:
--
作者:
M. Fisz
通讯作者:
M. Fisz