On the Population Diversity for the Chaotic Differential Evolution
Roman Šenkeřík, Adam Viktorin, Michal Pluháček, Tomáš Kadavý · 2018
This research deals with the modern and popular hybridization of chaotic dynamics and evolutionary computation. Unlike many research studies on the combination of chaos and metaheuristics, this paper focuses on the deeper insight into the population dynamics, specifically influence of chaotic sequences on the population diversity. The optimization algorithm performance was recorded as well. Experiments are focused on the extensive investigation of the different randomization schemes for the selection of individuals in a simple parameter adaptive Differential Evolution (DE) strategy: jDE algorithm. The jDE was driven by the nine different two-dimensional discrete chaotic systems, as the chaotic pseudo-random number generators. The population diversity and jDE convergence are recorded on the two-dimensional settings (10D and 30D) and 15 test functions from the CEC 2015 benchmark.