A hybrid flower pollination algorithm（HFPA）is proposed

aiming at the problem of slow convergence rate and low precision of flower pollination algorithm.The algorithm uses the uniform initialization and border variation to increase the population diversity

uses normal distribution zoom for global optimizing

to improve convergence speed.Local optimizing imports mutation strategy into factor to help algorithm jumping out of local optimum.The experiment uses seven test functions to compare with FPA and other group intelligent algorithms

the result shows that the HFPA has a significant improvement in convergence speed and optimizaing precision.