Parameter control mechanisms in differential evolution: A tutorial review and taxonomy

Differential evolution (DE) is a promising algorithm for continuous optimization. Its two parameters, CR and F, have great effect on the algorithm performance. In recent years many DE algorithms with parameter control mechanisms were proposed. In this paper we propose a taxonomy to classify these algorithms according to the number of candidate parameter values, the number of parameter values used in a single generation, and the source of considered information. We classify twenty-three recent studies into nine categories and review their design features. Two types of relationships between these algorithms and several research directions are also summarized.