期刊名称：International Journal of Advanced Networking and Applications
电子版ISSN：0975-0290
出版年度：2012
卷号：3
期号：6
页码：1450-1455
出版社：Eswar Publications
摘要：The existing clustering algorithm has a sequential execution of the data. The speed of the execution is very less and more time is taken for the execution of a single data. A new algorithm Parallel Implementation of Genetic Algorithm using K-Means Clustering (PIGAKM) is proposed to overcome the existing al gorithm. PIGAKM is inspired by using KM clustering over GA. This process indicates that, while using KM algorithm, it covers the local minima and it initialization is normall y done randomly, by KM and GA. It always converge the global optimum eventually by PIGAKM. To speed up GA process, the evalution is done parallely not individuall y. To show the performance and efficiency of this algorithms, the comparative study of this algorithm has been done
