Tabu Particle Swarm Optimization Algorithm Based on Dynamic Disturbance Term

QIAO Pei-li; SUN Chun-yu; LUO Zhi-yong(

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Tabu Particle Swarm Optimization Algorithm Based on Dynamic Disturbance Term

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- Tabu Particle Swarm Optimization Algorithm Based on Dynamic Disturbance Term
- Vol. 17, Issue 3, Pages: 87-90(2012)
- 作者机构：
  
  哈尔滨理工大学计算机科学与技术学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP301.6
- Published：2012
- 稿件说明：
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QIAO Pei-li, SUN Chun-yu, LUO Zhi-yong(. Tabu Particle Swarm Optimization Algorithm Based on Dynamic Disturbance Term[J]. 2012, 17(3): 87-90.
DOI：

QIAO Pei-li, SUN Chun-yu, LUO Zhi-yong(. Tabu Particle Swarm Optimization Algorithm Based on Dynamic Disturbance Term[J]. 2012, 17(3): 87-90. DOI：

摘要

针对粒子群优化算法后期收敛速度慢

且容易陷入局部最优解的缺点

在算法中加入动态扰动项

改变了速度的更新公式

使粒子可以跳出局部极值.后期引入禁忌搜索算法

充分利用禁忌搜索的记忆能力和爬上能力

能够快速搜索到全局最优解.通过对测试函数的仿真实验表明

采用动态扰动项的禁忌粒子群优化算法更能提高收敛速度

获得全局最优解. 更多还原

Abstract

To solve the problem that the particle swarm optimization has slow convergence rate and easy to trap into local optimum

we brought forward a method based on dynamic disturbance term and changed the speed formula that the particle can jump out local optimum.Introducing the tabu search algorithm in later period

we make full use of search memory and good hill-climbing ability that can quickly search the global optimal solution.Simulation experiments show that the Tabu Particle Swarm Optimization Al...

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