A Heuristic Immune-Genetic Algorithm for Multimodal Function Optimization

Author

Li, Yua Nyuan ; Dai, Yongshou ; Ma, Xigeng

Author_Institution

Coll. of Inf. & Control Eng., Univ. of Pet.

Volume

2

fYear

2005

fDate

28-30 Nov. 2005

Firstpage

36

Lastpage

40

Abstract

To avoid premature convergence and guarantee the diversity of the population, a heuristic immune-genetic algorithm (HIGA) is proposed. Rapid immune response (secondary response), adaptive mutation and density operators in the HIGA are emphatically designed to improve the searching ability, greatly increase the converging speed, and avoid locating the local maxima due to the premature convergence. The simulation results show that HIGA converges rapidly, guarantees the diversity, stability and good searching ability

Keywords

convergence; genetic algorithms; search problems; adaptive mutation; density operator; heuristic immune-genetic algorithm; multimodal function optimization; premature convergence; Control engineering; Convergence; Educational institutions; Genetic algorithms; Genetic mutations; Heuristic algorithms; Immune system; Intelligent agent; Petroleum; Stability;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on

Conference_Location

Vienna

Print_ISBN

0-7695-2504-0

Type

conf

DOI

10.1109/CIMCA.2005.1631442

Filename

1631442