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混沌粒子群优化算法及其在平面选址问题上的应用 被引量：4

Particle Swarm Optimization Algorithm with Chaos and Its Application in Planar Location Problem
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摘要 通过引入混沌来影响粒子速度的更新,构造出一种混沌粒子群优化算法.其主要思想是用混沌迭代引导个体进一步优化,从而避免群体陷入局部最优,而且收敛速度得到加快.通过对三个测试函数以及平面选址问题的求解,验证该算法具有非常好的性能. A kind of particle swarm optimization algorithm with chaos is constructed by adding chaos to influence the update of the velocities of particles. The main idea is to guide individual further optimization by chaos iterations. The technique can either avoid that the population trap into the local optimum or accelerate the convergence rate. It has better application in planar location problem.
作者 张滨燕 陈照辉 李大卫
机构地区 河南职业技术学院信息工程系 鞍山科技大学理学院
出处 《河南科学》 2006年第5期707-710,共4页 Henan Science
关键词 粒子群算法 混沌 随机搜索 测试函数 平面选址 particle swarm algorithm chaos stochastic searching test function planar location problem
分类号 TP18 [自动化与计算机技术—控制理论与控制工程]
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参考文献8

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共引文献13

同被引文献33

引证文献4

二级引证文献10

河南科学
2006年 第5期

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