Title :
A gradient-guided niching method in genetic algorithm for solving continuous optimisation problems
Author :
Peng, Jian Xun ; Thompson, Steve ; Li, Kang
Author_Institution :
Sch. of Mech. & Manuf. Eng., Queen´´s Univ., Belfast, UK
Abstract :
A hybrid genetic algorithm, which embeds a gradient-based local search route into a niching genetic algorithm, is proposed for solving continuous optimisation problems. The optimisation algorithm is applied to three nonlinear functions each having up to 100 variables and multi-minima. The test results show that relative to a standard niching algorithm the combination of a gradient-based search and niching improves the searching precision by several orders and the capability for locating the global optimum is significantly improved.
Keywords :
genetic algorithms; gradient methods; search problems; gradient search; hybrid genetic algorithm; multimodal optimisation; niching algorithm; Costs; Erbium; Genetic algorithms; Genetic engineering; Manufacturing; Nonlinear equations; Optimization methods; Power generation economics; Search methods; Testing;
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
DOI :
10.1109/WCICA.2002.1020151
