关键词: 花授粉算法, 群智能算法, 高斯变异, 动态调整

Abstract: Aiming at the shortages of basic flower pollination algorithm with easy to fall into local optimum, slow convergence speed and low search precision, a new algorithm based on dynamic adjustment and cooperative search（FPADC） is proposed. Halton sequences are used to enhance the quality of initial solution. Through the division of population, the diversity of the population can be improved to jump out of the local optimum. In order to improve the convergence rate and precision, optimizing strategy of the algorithms is dynamically adjusted according to the population evolutionary information. The experimental results show that the proposed algorithm is much better than basic FPA and its several improved algorithms in optimization performance.

Key words: flower pollination algorithm, swarm intelligent algorithm, Gauss mutation, dynamic tuning