Title :
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
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;
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
DOI :
10.1109/CIMCA.2005.1631421