Title :
Study on a novel hybrid adaptive genetic algorithm embedding conjugate gradient algorithm
Author :
Pan, Wang ; Zhun, Fan ; Shan, Feng ; Yun, Zhou
Author_Institution :
Huazhong Univ. of Sci. & Technol., Wuhan, China
fDate :
6/22/1905 12:00:00 AM
Abstract :
A hybrid adaptive genetic algorithm embedding conjugate gradient algorithm-conjugate gradient-adaptive evolutionary algorithm (CG-AGA) that combines the merit of the conjugate gradient algorithm is put forward in the paper. Compared with the conventional evolutionary algorithm, the new algorithm (CG-AEA) is more efficient in local searching, which is the major weak point of the conventional algorithm. Experiments have demonstrated the satisfactory speed and precision of CG-AEA
Keywords :
conjugate gradient methods; genetic algorithms; search problems; conjugate gradient-adaptive evolutionary algorithm; hybrid adaptive genetic algorithm; local searching; Algorithm design and analysis; Chaos; Evolutionary computation; Genetic algorithms; Genetic mutations; Information analysis; Optimization methods; Size control; Symmetric matrices;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.860048
