多策略增强花授粉算法及其应用

lassic flower pollination algorithm (FPA) can be easily exposed to the shortcomings of local optimal solution and slow convergence velocity. In view of these shortcomings, this paper proposed an FPA with an enhanced lens imaging strategy and random neighborhood-based mutation strategy. The lens imaging strategy can help the algorithm avoid the shortcoming of local optimal solution by expanding the search space of FPA to increase the diversity of the solution. The introduction of random neighborhood-based mutation strategy can enhance the convergence accuracy and search speed of the algorithm by guiding algorithm search with information in the neighborhood. A comparison of the improved FPA with four other improved algorithms on CEC2013 test function found that the improved multi-strategy FPA performs better than the comparison algorithms in both convergence accuracy and search speed. To study its practical utility, this paper applies the multi-strategy FPA into the automobile transmission parameter model and the results indicate that multi-strategy FPA is better than the comparison algorithm in optimization of automobile transmission parameters.