计算机科学 ›› 2012, Vol. 39 ›› Issue (6): 198-200.
• 人工智能 • 上一篇 下一篇
王正帅,邓喀中
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摘要: 提出了随机粒子群优化算法(rPSO),并将其与标准PSO纳入到文化算法(CA)框架中,建立了基于文化框架的随机粒子群优化算法(CA-rPSO}。该算法以rPSO作为信念空间的进化算法,以PSO作为群体空间的进化算法,形成了两者独立并行进化的“双演化双促进”机制。选取J个测试函数进行了仿真实验分析并与其他算法进行了比较,结果表明CA-rPSO的寻优性能得到显著提高,且算法简单、易于实现。
关键词: 粒子群优化,随机扰动,文化算法
Abstract: Bringing standard PSO and random particle swarm optimization(rPSO ) proposed in the paper into the framework of cultural algorithm(CA) , a novel optimization method named random particle swarm optimization based on cultural algorithm(CA-rPSO) was established. In CA-rPSO, the evolving algorithms of belief space and the population space were represented with rPSO and PSO respectivcly,forming independent and parallel "dual evolution-dual promolion" mechanism. 5 testing functions were selected to simulate and analyze CA-rPSO. The result shows that optimization performance of CA-rPSO is obviously promoted and the algorithm is simple and easy to carry out.
Key words: Particle swarm optimization,Random disturbance,Cultural algorithm
王正帅,邓喀中. 基于文化框架的随机粒子群优化算法[J]. 计算机科学, 2012, 39(6): 198-200. https://doi.org/
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