Dragonfly algorithm is a kind of new intelligent algorithm based on the Dragonfly foraging food and evading predators

but there is also existing rough precision and slow convergence. In order to improve the precision of the algorithm and reduce the blindness search

this paper proposes a dragonfly algorithm based on differential evolution strategy

called DEDA. In late iteration

we introduce differential evolution into the next generation which could increase the diversity of the population. At last

we applied DEDA to solve six complex functions

and compared it with basic dragonfly algorithm from the results

the experimental results show that DEDA on solving complex function optimization problems have a certain advantage.