Mind evolutionary computation with swarm intelligence

Author

Qiao, Gang-Zhu ; Jie, Jing ; Zeng, Jian-chao ; He, Xiao-Juan

Author_Institution

Div. of Syst. Simulation & Comput. Application, Taiyuan Heavy Machinery Inst., China

Volume

4

fYear

2004

fDate

26-29 Aug. 2004

Firstpage

2172

Abstract

Mind evolutionary computation (MEC) is a novel stochastic algorithm that derived from man´s swarm intelligence. Based on the swarm theory, the social behavior analysis about MEC is made and the searching mechanisms of its operators are studied. After that, a parameter analysis is provided for the similar axis operator, and a cooperation-based dissimilation operator (CDO) is developed. Finally, a series of experiments have been done to make a parameter choice and an evaluation for MEC. The results illustrate MEC with CDO is a viable global optimization method owning robust ability.

Keywords

artificial intelligence; evolutionary computation; stochastic processes; cooperation-based dissimilation operator; global optimization; mind evolutionary computation; stochastic algorithm; swarm intelligence; Algorithm design and analysis; Analytical models; Biological system modeling; Biology computing; Computational modeling; Evolution (biology); Evolutionary computation; Optimization methods; Particle swarm optimization; Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on

Print_ISBN

0-7803-8403-2

Type

conf

DOI

10.1109/ICMLC.2004.1382158

Filename

1382158