Differential evolution, jDE, Scale factor, Crossover ratio, Experi-mental study, Real-world problems, CEC 2017 benchmark set.

Proper settings of two control parameters in differential evolution (DE) algorithm play a crucial role when solving various optimisation problems. There are a lot of investigated adaptive mechanisms sampling the values of these pa-rameters differently. In the proposed adaptive approach, efficient and inefficient settings of main DE control parameters are considered. A sampling of the control parameters is performed using the performance of parameters’ settings achieved in a preliminary experimental study. The proposed approach is applied to a fre-quently used adaptive jDE algorithm. The statistical analysis of the results pro-vides better information about the efficiency of the proposed technique. More proper settings in the adaptation of DE control parameters provide better performance than a more general approach when solving CEC 2017 problems.