摘要
针对优化过程中出现的求解精度低、收敛速度慢等问题,提出一种改进混合蛙跳算法。在种群个体位置更新过程中,基于数学中二分法查找的思想,引入中间因子和加速因子。通过引入中间因子,调控青蛙个体在寻优过程中的步长,扩大算法的局部搜索范围,从而保持青蛙种群的多样性;引入加速因子,加快蛙的搜索速度。对6个测试函数的实验表明,改进后的混合蛙跳算法具有更高的求解能力、收敛精度和更快的收敛速度。
Aiming at the problems of low accuracy and slow convergence in the optimization process,an improved hybrid leapfrog algorithm is proposed.In the update process of population individual position,intermediate factors and acceleration factors are introduced based on the dichotomy in mathematics.The intermediate factor is introduced to adjust the step length of frog individuals in the search process and expand the local search range of the algorithm in order to keep the diversity of the frog populations.Acceleration factor is introduced to speed up the search speed of frogs.The experiments on six test functions show that the improved hybrid leapfrog algorithm has higher problem-solving ability,convergence accuracy and faster convergence speed.
作者
王晓彬
邹海荣(指导)
WANG Xiaobin;ZOU Hairong(School of Electrical Engineering,Shanghai Dianji University,Shanghai 201306,China)
出处
《上海电机学院学报》
2021年第5期267-273,共7页
Journal of Shanghai Dianji University
关键词
混合蛙跳算法
二分法查找
加速因子
局部搜索范围
hybrid leapfrog algorithm
binary search
acceleration factor
local search range
