基于混合策略改进的花朵授粉算法

针对传统花朵授粉算法(FPA)在解决复杂问题时搜索精度低和收敛速度慢等问题，提出了一种基于混合策略改进的花朵授粉算法(HSFPA)。采用自适应转换概率策略改进转换概率，动态平衡全局授粉和局部授粉之间的关系；在全局授粉阶段，提出一种动态全局搜索策略，既可以加快算法收敛速度，又能增加花粉种群的多样性，防止花粉陷入局部最优；局部搜索增强策略使得花粉能够充分开发当前优质花粉周围的搜索空间，提高收敛精度；花粉越界修正策略进一步加强了算法的探索能力。通过对10个基准函数进行仿真测试，实验结果表明，HSFPA算法在搜索速度和寻优精度方面具有更好的效果。

Flower pollination algorithm based on hybrid strategy

Aiming at the problems of low search accuracy and slow convergence speed of traditional flower pollination algorithm(FPA) in solving complex problems, this paper proposed an improved flower pollination algorithm based on hybrid strategy(HSFPA). It adopted adaptive transition probability strategy to improve the transition probability and dynamically balance the relationship between global pollination and local pollination. In the stage of global pollination, it proposed a dynamic global search strategy, which could not only accelerate the convergence speed of the algorithm, but also increase the diversity of pollen population and prevented pollen from falling into local optimization. The local search enhancement strategy enabled pollen to fully develop the search space around the current high-quality pollen and improved the convergence accuracy. Pollen cross-border correction strategy further strengthened the exploration ability of the algorithm. Through the simulation test of 10 benchmark functions, the experimental results show that the HSFPA algorithm has better effect in search speed and optimization accuracy.