摘要
传统花朵授粉算法具有收敛精度低,后期收敛速度慢,易陷入局部最优的缺点。针对这些问题,本文提出了一种自适应t分布扰动的正余弦花朵授粉算法。该算法首先利用托普利兹矩阵划分解空间,使初始种群的个体均匀分布在解空间;然后引入正余弦算子对基本花朵授粉算法的局部搜索部分进行改进;最后提出一种自适应t分布扰动来帮助算法跳出局部最优解。在10个标准测试函数上进行实验的结果表明,自适应t分布扰动的正余弦花朵授粉算法具有较快的收敛速度,较高的收敛精度,较好的鲁棒性以及跳出局部最优解的能力,优于基本花朵授粉算法与其他几种相关群智能算法,是解决复杂高维函数问题的有效方法。
The traditional flower pollination algorithm has the disadvantages of low convergence accuracy, slow convergence speed and easy to fall into local optimum. In order to solve these problems, this paper proposes a sine/cosine flower pollination algorithm with adaptive t-distribution disturbance. First, Toeplitz matrix is used to divide the solution space so that the individuals of the initial population are evenly distributed in the solution space;Second, sine/cosine operator is introduced to improve the local search part of the basic flower pollination algorithm;Third, an adaptive t-distribution perturbation is proposed to help the algorithm jump out of the local optimal solution. Experiments are carried out on ten standard test functions. The results show that the algorithm generally has faster convergence speed, higher convergence accuracy, better robustness and the ability to jump out of the local optimal solution. It is superior to the basic flower pollination algorithm and other two swarm intelligence algorithms. It is an effective method to solve complex high-dimensional function problems.
作者
周佳毅
钱谦
冯勇
伏云发
Zhou Jiayi;Qian Qian;Feng Yong;Fu Yunfa(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China;Yunnan Key Laboratory of Computer Technology Applications(Kunming University of Science and Technology),Kunming 650500,China)
出处
《科技通报》
2022年第3期52-61,71,共11页
Bulletin of Science and Technology
基金
国家自然科学基金委员会地区基金(32060193)
云南省基础研究计划项目(202101AT070082)
云南计算机技术应用重点实验室开放基金。
关键词
花朵授粉算法
函数优化
正弦余弦算法
自适应扰动
flower pollination algorithm
function optimization
sine/cosine algorithm
adaptive disturbance
