Abstract: In this paper, Reverse fruit fly optimization algorithm of optimal wavelet transfer(WTRFOA) is proposed to solve the problem that the fruit fly optimization algorithm(FOA) is easy to fall into the local optimum, which leads to the slow convergence rate and the low precision. By analyzing the limitation of the fruit fly algorithm only moving to the optimal individual, the strategy, naming escape mechanism of the wavelet transfer, is proposed to ensure the correctness of the iterative direction selection. Carrying out the reverse wavelet transfer when the population diversity is low, to guide the population to escape from the local limit Converges to the global optimal solution. Simulation results was shown that the new algorithm can effectively keep the optimal evolution direction of the population, suppress the algorithm into the local optimum and have good optimization performance.