An adaptive variant of jSO with multiple crossover strategies employing Eigen transformation

In this paper, new strategy options are developed for the adaptive jSO algorithm. The proposed variant of jSO is based on the competition of a binomial and exponential crossover. Moreover, an Eigen transformation approach is employed in the selected crossover with a given probability. The proposed variant of jSO is applied to the CEC 2022 benchmark set, which contains 12 functions with dimensionality $D=10$, 20. The proposed algorithm found the optima values in seven problems out of 24. When comparing the new variant of jSO with the original jSO algorithm, nine functions were improved, where two of them significantly.