Enhancing exploration in differential evolution via exponential recombination

摘要

In recent years, many new variants of Differential Evolution (DE) have been proposed for real number function optimization, and most of these variants employ binomial recombination as their crossover operators. By contrast, another classical crossover operator, exponential recombination, received less attention. This paper examines the explorative ability of exponential recombination in handling high-dimensional multimodal problems. Based on the analysis, a new variant of DE with a hybrid crossover operation is proposed. DE/best/1, a greedy mutation strategy rarely used in tackling multimodal problems, is utilized in our algorithm to help combine the two basic recombination operators. Empirical results demonstrate that the proposed algorithm is powerful in solving high-dimensional multimodal problems.