  Differential evolution(DE) is a conventional algorithm with fast convergence
speed. However, DE may be trapped in local optimal solution easily. Many
researchers devote themselves to improving DE. In our previously work, whale
swarm algorithm have shown its strong searching performance due to its niching
based mutation strategy. Based on this fact, we propose a new DE algorithm
called DE with Better and Nearest option (NbDE). In order to evaluate the
performance of NbDE, NbDE is compared with several meta-heuristic algorithms on
nine classical benchmark test functions with different dimensions. The results
show that NbDE outperforms other algorithms in convergence speed and accuracy.
