Differential Evolution Enhanced with Multiple Dimensional Scaling
Minjuan Liu, Wei Huang · 2019
Differential evolution algorithm is a well-known intelligent optimization algorithm. In the search process, the algorithm tends to converge prematurely, making the population trapped in local optima. To solve this problem, this paper proposes a new differential evolution algorithm based on multiple dimensional scaling (MDS). We tested the performance of the algorithm on 11 benchmark functions. Experimental results show that the proposed algorithm can achieve higher accuracy when compared with some other evolutionary algorithms reported in the literatures.