On the parameter settings for the chaotic dynamics embedded differential evolution

This research deals with the hybridization of the two softcomputing fields, which are chaos theory and evolutionary computation. This paper aims on the experimental investigations on the chaos-driven evolutionary algorithm Differential Evolution (DE) concept. This research represents the continuation of the preliminary satisfactory results obtained by means of chaos embedded (driven) DE, which utilizes the chaotic dynamics in the place of pseudorandom number generators The novelty of this work represents the experimental analysis of the chaotic dynamics directly injected into the DE. To be more precise, this research investigates the influence of parameter settings to the performance of chaos driven DE. Both settings for mutation and crossover DE control parameters and adjustable chaotic system parameters are experimentally investigated here. Repeated simulations were performed on the selected set of well-known benchmark functions in higher dimensions. Finally, the obtained results are compared with canonical DE and state-of-the art representative of basic adaptive variant jDE.