Data optimization with differential evolution strategies: A survey of the state-of-the-art

摘要

In the optimization filed, there are various proposed algorithms and Differential Evolution (DE) is one of the most effective ones. Among the latter, there is need for more effective and efficient techniques, and strategies. Although most of these algorithms have demonstrated very good performance, but they still suffer from slow convergence rate. This paper reviews the DE, all its strategies, techniques, and some important algorithms.