Title :
A novel survival of the fittest genetic algorithm
Author :
Pan, Fengping ; Sun, Xiaoyan ; Xu, Shifan ; Guo, Xijin ; Gong, Dunwei
Author_Institution :
Coll. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Jiangxi, China
Abstract :
Considering the relationship between the variety of evolution population and evolution times, a novel closed crossing avoidance strategy is put forth in this paper. Based on it, a novel survival of the fittest genetic algorithm is present. The algorithm can avoid close breeding effectively and the thought of survival of the fittest is externalized. It has been proved that the algorithm can converge to an optimal solution globally. Simulation shows that the algorithm present in this paper is an efficient contrast with the simple genetic algorithm.
Keywords :
convergence; genetic algorithms; close breeding; closed crossing avoidance strategy; convergence; evolution population; genetic algorithm; simulation; survival of the fittest; Automation; Educational institutions; Electronic mail; Genetic algorithms; Intelligent control; Sun;
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
DOI :
10.1109/WCICA.2002.1021395