Comparative Study of Modern Differential Evolution Algorithms: Perspectives on Mechanisms and Performance

Since the discovery of the Differential Evolution algorithm, new and improved versions have continuously emerged. In this paper, we review selected algorithms based on Differential Evolution proposed in recent years. We examine the mechanisms integrated into them and compare the performances of algorithms. To compare their performances statistical comparisons were used as they enable us to draw reliable conclusions about algorithms performances. We use the Wilcoxon signed-rank test for pairwise comparisons and the Friedman test for multiple comparisons. Subsequently, the Mann-Whitney U test was added. We conducted not only a cumulative analysis of algorithms but we also focused on their performances regarding the function family (i.e., unimodal, multimodal, hybrid, and composition functions). Experimental results of algorithms were obtained on problems defined for the CEC’24 Special Session and Competition on Single Objective Real Parameter Numerical Optimization. Problem dimensions of 10, 30, 50, and 100 were analyzed. In this paper we highlight promising mechanisms for further development and improvements, based on the performed study of the selected algorithms.