In the process of applying traditional simulated annealing algorithm and tabu search algorithm to solving multi-peak complex functions

the following problems often occur:particles converge to the local optimal solution too fast

the late converge slows down and search ability turns poor.In order to solve these problems

the definition of function complexity is proposed

and adaptive simulated annealing algorithm and tabu search algorithm are presented based on the function complexity.In these algorithms

the step length control parameters are adaptively adjusted according to the function complexity;then rough solution of the function is obtained in terms of regulated step length;finally

and the original step length is used to acquire the global optimal solution.Experiments show that the proposed method cannot only transcend the limits of the local optimal solution

but also reduce iteration of the above algorithms

and efficiently improve local and global search ability.