In order to overcome the basic artifical firefly algorithm(GSO) in solving problems of low precision for the multi peak function

high dimension and slow convergence. Thus

this paper comes up with a Dynamic step optimization algorithm. During the iteration

the step decrease nonlinearly. At the beginning of the optimization maintains a large step to search optimal value

enhancing global optimization ability. At the ending of it

optimization maintains a small step to improve ablity of local searching. In addition

original firely algorithm does not move anywhere

when Nit is null. this paper makes it move somewhere randomly. With it

This algorithm can avoid being mature and falling into a local value. As the same time

improved GSO can achieve a higher accuracy during Iterative process.

comparing with GSO and reference literature alogorithm ASGSO. According to the simulation experiment

it shows that to some extent

the improved algorithm on covergence speend and precision are enhanced.