期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2016
卷号：5
期号：2
页码：0293-0295
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Genetic algorithms (GA) are a type of evolutionary algorithms based on the principle of natural evolution and heredity. Genetic algorithm works in the same way as nature does. In this paper, GA is described using De Jongs' benchmark Function example for function optimization with different selection techniques. The fitness value of function for different number of generations is compared keeping all other parameters constant, except the selection techniques i.e. roulette wheel and roulette wheel with elitism. The results show that roulette wheel with elitism gives better result than roulette wheel selection for function optimization.
