一种改进的基于进化状态的粒子群算法
首发时间:2010-04-27
摘要:本文借鉴聚类分析中聚类中心的概念,对基于进化状态估计的自适应粒子群算法中的进化因子进行改进,提出了一种新的计算进化因子的方法。该方法通过计算种群中各个粒子到种群中心位置的距离来计算进化因子。对优化函数的仿真实验表明,在大多数情况下,改进的基于进化状态估计的PSO算法取得了更好的优化效果,同时也提高了算法的运算速度。
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An Improved Particle Swarm Optimization Algorithm Based on Evolutionary State
Abstract:Utilizing the concept of the centroid in clustering analysis, this paper improves the evolutionary factor of the adaptive particle swarm optimization based on the concept of evolutionary state estimation, and proposes a novel method of computing the evolutionary factor. This method uses computing the distance between the particle and the centroid of the swarm to calculate the evolutionary factor. Through experiments on well known benchmarks, we can find out the improved PSO algorithm based on the concept of evolutionary state estimation has better performance in most instances, and accelerates the speed of running.
Keywords: Particle Swarm Optimization Evolutionary State Estimation Evolutionary factor Centroid of the Sswarm
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