关键词: 花授粉算法, 萤火虫算法, 最优解, 转换概率, 变异因子

Abstract: Flower pollination algorithm is a new metaheuristic algorithm for optimization, however, it can have some stagnation and thus a lower convergence rate under certain conditions, which can limit the search ability of the algorithm. For this reason and to improve the search efficiency, this paper proposes a self-adaptive mutation operator in the process of local pollination, self-adaptive adjustment of the switch probability, and hybridization of the flower pollination algorithm with the firefly algorithm, which leads to a new hybrid approach called self-adaptive flower pollination algorithm enhanced by the firefly algorithm. The proposed approach has been validated by benchmark functions and has been compared with other algorithms such as DE-FPA and PSO-FPA. Results indicate that the proposed hybrid algorithm has a higher rate of convergence and stability than other algorithms.

Key words: Flower Pollination Algorithm（FPA）, Firefly Algorithm（FA）, optimal solution, switch probability; , mutation operator