A hybrid differential evolutionary algorithm based on the hierarchical clustering
Zheng Fang, Ming Yang, Guilin Zhang, Jing Guan · 2016
The unconstrained global optimization algorithm has great applicability. Differential Evolution is widely used to solve the unconstrained global optimization problem. In this paper, we present a Hierarchical Clustering Differential Evolution Algorithm (HCDE), which combines Hierarchical Clustering and Differential Evolution. We cluster the population of Differential Evolution Algorithm every K generations. Then updating current population by population update strategy. The HCDE is tested by 30 test problems, the good or excellent performance of HCDE has been verified by comparing with other improved DE algorithms.