Title :
Genetic algorithms in noisy environment
Author :
Then, T.W. ; Chong, Edwin K P
Author_Institution :
Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA
Abstract :
Genetic algorithms (GA) have been widely used in the areas of function optimization and machine learning. In many of these applications, the effect of noise is a critical factor in the performance of the genetic algorithms. In this paper, we propose an effective method for obtaining the optimal solution by using an optimal solution list and systematically changing certain parameters of the algorithm. Our results show that the optimal solution list is able to provide a small solution set that contains near optimal solutions
Keywords :
genetic algorithms; learning (artificial intelligence); noise; function optimization; genetic algorithms; machine learning; noisy environment; optimal solution list; Gaussian noise; Genetic algorithms; Genetic mutations; Machine learning; Machine learning algorithms; Sampling methods; Virtual manufacturing; Working environment noise;
Conference_Titel :
Intelligent Control, 1994., Proceedings of the 1994 IEEE International Symposium on
Conference_Location :
Columbus, OH
Print_ISBN :
0-7803-1990-7
DOI :
10.1109/ISIC.1994.367813
