In this paper we investigate several self-adaptive mechanisms to improve our previous work on NSDE , which is a recent DE variant for numerical optimization. The selfadaptive methods originate from another DE variant, SaDE , but are remarkably modified and extended to fit our NSDE. And thus a Self-adaptive NSDE (SaNSDE) is proposed to improve NSDE's performance. Three self-adaptive mechanisms are utilized in SaNSDE: self-adaptation for two candidate mutation strategies, self-adaptations for controlling scale factor F and crossover rate CR, respectively. Experimental studies are carried out on a broad range of different benchmark functions, and the proposed SaNSDE has shown significant superiority over NSDE. © 2008 IEEE.
|Title of host publication
|2008 IEEE Congress on Evolutionary Computation, CEC 2008
|Number of pages
|Published - Jun 2008