Hierarchical Competitive Differential Evolution for Global Optimization

Global search is a fundamental task in optimization, aiming to find the optimal solution across the entire search space. To address the challenges in global search, a hierarchical competitive differential evolution algorithm is proposed. It uniquely incorporates a hierarchical competition mechanism and an adaptive differential mutation strategy based on competition outcomes, substantially enhancing global search. The proposed algorithm benchmarks on a total of 30 international test functions of CEC 2017 benchmark functions. The convergence accuracy, coupled with the outcomes of two nonparametric statistical tests, the Friedman test and the Wilcoxon signed-rank test, clearly demonstrates that HCDE exhibits competitive performance when compared to the other 14 efficient optimizers.