Differential evolutionary strategies for global optimization
Chen Guang Xu · JOURNAL OF SHENZHEN UNIVERSITY SCIENCE AND ENGINEERING · 2008
A new algorithm,differential evolutionary strategies(DES),for the high-dimensional continuous function optimization,was proposed.The proposed algorithm was designed by making use of both the strong global search capability of differential evolutionary strategies and the rapidly converging capability of evolution strategies.Computer simulations were tested on several high-dimensional continuous function optimization problems,and the results indicate that the proposed algorithm improves the efficiency and is much more robust than conventional evolutionary strategies.The proposed algorithm can be used in biological evolution researching,machine learning,artificial intelligence,fuzzy system,artificial neural network training etc.,especially in digital signal processing,data mining and multi-programming.