International Technical Conference on Circuits/Systems, Computers and Communications
WS model based Massively Parallel Genetic Algorithm and its Various Applications
Kotaro Maekawa, Hajime Nobuhara ,
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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.