Linh Tao
D. Functional Control System, Shibaura Institute of Technology, Japan
Hieu Pham
National Institute of Patent and Technology Exploitation, Vietnam
Hiroshi Hasegawa
D. Functional Control System, Shibaura Institute of Technology, Japan
Ladda ner artikel
http://dx.doi.org/10.3384/ecp17142533Ingår i: Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016
Linköping Electronic Conference Proceedings 142:77, s. 533-539
Publicerad: 2018-12-19
ISBN: 978-91-7685-399-3
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
A new evolutionary algorithm called NN-DEGA that using Arti?cial Neural Network (ANN) for Self-adaptive Differential Evolution (DE) with Island model of Genetic Algorithm (GA) is proposed to solve large scale optimization problems, to reduce calculation cost, and to improve stability of convergence towards the optimal solution. This is an approach that combines the global search ability of DE and the local search ability of Adaptive System with Island model of GA. The proposed algorithm incorporates concept from DE, GA, and Neural Networks (NN) for self-adaptive of control parameters. The NN-DEGA is applied to several benchmark tests with multi-dimensions to evaluate its performance. It is shown to be statistically signi?cantly superior to other Evolutionary Algorithms (EAs), and Memetic Algorithms (MAs).
differential evolution, memetic algorithm, migration, neural network, parallel genetic algorithm
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