An Improved Flower Pollination Algorithm Based on Muti-population Co-evolutionary Strategy to Solve Function Optimization Problems

摘要

Flower pollination algorithm is an algorithm that simulates the behavior of flower pollination in the biological world. In order to refine the accuracy of the FPA algorithm and effectively improve the convergence speed of the original algorithm FPA, two improved flower pollination algorithms based on clonal operator and bacterial foraging strategy are proposed. Then, based on the synergistic strategy between organisms, the muti-population co-evolutionary flower pollination algorithm (CFPA) was proposed and applied to the proposed two improved FPAs. Finally, this article designs a simulation experiment and uses six typical functions to carry out. According to the experimental data, the improved algorithm proposed in this paper has significantly improved the convergence speed of the algorithm and the optimization accuracy of the experimental results.