A New Differential Evolution with self-terminating ability using fuzzy control and k-nearest neighbors

A new Differential Evolution (DE) that incorporates fuzzy control and k-nearest neighbors algorithm to determine the terminating condition is proposed. A technique called Iteration Windows is introduced to govern the number of iteration in each searching stage. The size of the iteration windows is controlled by a fuzzy controller, which uses the information provided by the k-nearest neighbors system to analyze the population during the searching process. The controller keeps controlling the iteration windows until the end of the searching process. The wavelet based mutation process is embedded in the DE searching process to enhance the searching performance of DE. The F weight of DE is also controlled by the fuzzy controller to further speed up the searching process. A suite of benchmark test functions is employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method can terminate the searching process with a reasonable number of iteration.