Summary

International Technical Conference on Circuits/Systems, Computers and Communications

2016

Session Number:M2-6

Session:

Number:M2-6-3

WS model based Massively Parallel Genetic Algorithm and its Various Applications

Kotaro Maekawa,  Hajime Nobuhara ,  

pp.229-232

Publication Date:2016/7/10

Online ISSN:2188-5079

DOI:10.34385/proc.61.M2-6-3

PDF download (1.8MB)

Summary:
Genetic algorithms are widely used method as solutions for optimization problems. However in complex conditions, it does not work properly. In this paper, to solve this problem, we propose WS model GA based on Massively Parallel Genetic Algorithm, which has diversity. The system is applied to Function optimizations, and a classroom optimization, and it's confirmed that WS model GA was better result than Standard GA and Massively Parallel Genetic Algorithm in complex experimental cases.