Title :
Implementation of PGAs in conjunction with fuzzy algorithm
Author :
Key Lou Kwon ; Alouani, A.T.
Author_Institution :
School of Information & Communication, Engineering Sungkyunkwan University, Suwon, Korea
Abstract :
Genetic algorithms(GA), which are based on the idea of natural selection and survival of the fittest, have proven successful in solving complex problems that are not easily solved through conventional methods. Parallel genetic algorithm(PGA) is an extension of the classical GA. The important aspect in PGA is migration and GA operation. This paper presents PGAs that use fuzzy algorithm and natural select concept to migration of subpopulations. Fuzzy algorithm is used to change GA operators. Experimental results show that the proposed methods exhibit good performance compared to the classical method.
Keywords :
Biological cells; Computational efficiency; Convergence; Electronics packaging; Genetic algorithms; NP-complete problem; Optimization methods; Parallel processing; Genetic algorithm; fuzzy algorithm; migration; parallel genetic algorithm;
Conference_Titel :
Machine Learning and Applications, 2004. Proceedings. 2004 International Conference on
Conference_Location :
Louisville, Kentucky, USA
Print_ISBN :
0-7803-8823-2
DOI :
10.1109/ICMLA.2004.1383551