Performance Improvement of Hybrid Real-Coded Genetic Algorithm with Local Search and Its Applications

Author

Zhang, Hong ; Ishikawa, Masumi

Author_Institution

Dept. of Brain Sci. & Eng., Kyushu Inst. of Technol., Kitakyushu

Volume

1

fYear

2005

fDate

28-30 Nov. 2005

Firstpage

1171

Lastpage

1176

Abstract

We have already proposed a hybrid real-coded genetic algorithm with local search (HRGA/LS) for improving the search performance of a real-coded genetic algorithm. To further improve the search performance of HRGA/LS, this paper proposes to use the blend crossover, BLX-alpha, instead of simple crossover. It is expected to find still better solutions by increasing the diversity of generated individuals. Simulation experiments elucidate the characteristics of group search of HRGA/LS with BLX-alpha, and demonstrate that the proposed method vastly improves search performance

Keywords

genetic algorithms; mathematical operators; search problems; blend crossover operator; hybrid real-coded genetic algorithm; local search problem; search performance; Biological cells; Biological neural networks; Data mining; Genetic algorithms; Genetic engineering; Genetic mutations; Large-scale systems; Noise robustness; Pattern classification; Portfolios;

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.2005.1631421

Filename

1631421