ASYNCHRONOUS PARALLEL EVOLUTIONARY ALGORITHM FOR FUNCTION OPTIMIZATION

A new efficient asynchronous parallel evolutionary algorithm for function optimization is proposed in this paper. Using this algorithm, some hard optimization problems including a very high dimensional BUMP problem are solved. Because of the super nonlinear and super multimodal characteristics of BUMP problem, there are no results with dimension greater than 50 ever published until now. In spite of these, not only a series of best solutions from 2 to 50 dimensions but also satisfactory results up to 1000000 dimensional BUMP problem have been obtained. The numerical results show that the new asynchronous parallel evolutionary algorithm is robust, effective, and efficient.