Success-history based adaptive differential evolution algorithm with multi-chaotic framework for parent selection performance on CEC2014 benchmark set
Adam Viktorin, Michal Pluháček, Roman Šenkeřík · 2016
This paper presents a novel multi-chaotic framework, which is used for the parent selection process in Success-History based Adaptive Differential Evolution (SHADE) algorithm. Created variant of the Differential Evolution (DE) algorithm was named MC-SHADE and its performance is tested on the CEC2014 benchmark set in order to participate in the CEC2016 competition on bound constrained single objective numerical optimization - single parameter-operator set based case.