Monkey algorithm is a new optimization algorithm of swarm intelligent. The algorithm can effectively solve the optimization problems of functions such as linear, nonlinear, nonconvex and complex high dimensional function, etc. Currently, it has been widely studied and concerned by many scholars. In order to further improve the solution accuracy of monkey algorithm, this paper puts forward an improved monkey algorithm. Firstly, uniformly distributed Kent chaotic map is adopted as the initial feasible solution of the algorithm. Then, the descending factor is used as the step size in the climb process of the algorithm. Finally, in the simulation experiment, compared with the existing methods, the results show that the solution accuracy of the proposed monkey algorithm is significantly improved, namely, the proposed algorithm is feasible.