改进的向心加速度粒子群算法
首发时间:2019-02-14
摘要:CAPSO算法是近些年由Behesh改进的向心加速度粒子群算法ti和Zahra基于PSO算法和引力搜索算法提出来的一个新算法。本文在CAPSO算法的基础上引入了偏转角度和偏转半径两个参数来控制粒子的向心运动过程,从而使得算法在向心速度过程中探索的时间最少,进而使得陷入局部最优解的逃离速度增加,得到了改进后的ICAPSO算法。用算法对许多基准函数测试的实验结果表明,该方法调整了CAPSO算法在处理高维多峰问题上的缺陷,并对精度进行了一定提高。
关键词: CAPSO算法 引力搜索算法 偏转角度 偏转半径 基准函数
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Improvement of the centripetal-accelerated particles swarm optimization
Abstract:CAPSO algorithm is a new algorithm proposed by Beheshti and Zahra in recent years based on PSO algorithm and gravitational search algorithm. On the basis of CAPSO algorithm, two parameters, deflection angle and deflection radius, are introduced to control the centripetal motion process of particles, so that the searching time of the algorithm in the centripetal velocity process is minimized, and then the escape speed falling into the local optimal solution is increased. An improved ICAPSO algorithm is obtained. The experimental results of many benchmark functions tested by the algorithm show that the method adjusts the shortcomings of CAPSO algorithm in dealing with high-dimensional and multi-peak problems, and improves the accuracy to a certain extent.
Keywords: CAPSOalgorithm, GSA algorithm, deflection radius, deflection angle, benchmark functions.
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