Varying Number of Difference Vectors in Differential Evolution

Differential evolution (DE) has shown its effectiveness in solving many problems. The difference vector (DV), which serves as a measure for the dispersion of candidate solutions, has a key role in the adaptive mutation of DE. Traditionally, DE adopts one DV. In this paper, we investigate the use of more than one DV and propose the Poisson differential evolution (PDE) with a varying number of DVs based on Poisson distribution. Experimental results on 24 numerical benchmark functions point out the ineffectiveness of increasing DVs in the original DE. On the other hand, the results show that the proposed PDE can achieve significant improvement on DE in terms of solution quality and convergence speed, which validates the benefit of varying number of DVs for DE.