Title :
A combined adaptive bounding and adaptive mutation technique for genetic algorithms
Author :
Peng, Jianxun ; Li, Kang ; Thompson, Steve
Author_Institution :
Sch. of Mech. & Manuf. Eng., Queen´´s Univ., Belfast, UK
Abstract :
A combined adaptive bounding and adaptive mutation technique is proposed both to improve the solution precision and to increase the convergence rate of genetic algorithms for continuous optimization problems. The proposed technique is tested over two benchmark continuous functions, and the results show that the proposed technique is superior to simple GAs and GAPSSA.
Keywords :
convergence; genetic algorithms; search problems; adaptive bounding technique; adaptive mutation technique; benchmark continuous functions; continuous optimization problems; convergence rate; genetic algorithms; parameter space size adjustment; Benchmark testing; Biological cells; Convergence; Evolutionary computation; Genetic algorithms; Genetic engineering; Genetic mutations; Manufacturing; Search methods; Stochastic processes;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1341967
