| 动态粒子群优化算法 |
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| 引用本文： | 于雪晶,麻肖妃,夏斌. 动态粒子群优化算法[J]. 计算机工程, 2010, 36(4): 193-194 |
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| 作者姓名： | 于雪晶 麻肖妃 夏斌 |
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| 作者单位： | 1. 长春工业大学信息传播工程学院,长春,130012
2. 94580部队,蚌埠,233000 |
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| 摘 要： | 针对普通粒子群优化算法难以在动态环境下有效逼近最优位置的问题，提出一种动态粒子群优化算法。设置敏感粒子和响应阈值，当敏感粒子的适应度值变化超过响应阈值时，按一定比例重新初始化种群和粒子速度。设计双峰DF1动态模型，用于验证该算法的性能，仿真实验结果表明其动态极值跟踪能力较强。
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| 关 键 词： | 粒子群优化算法 动态 双峰DF1模型 敏感粒子 |
| 修稿时间： | |
Dynamic Particle Swarm Optimization Algorithm |
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| YU Xue-jing,MA Xiao-fei,XIA Bin. Dynamic Particle Swarm Optimization Algorithm[J]. Computer Engineering, 2010, 36(4): 193-194 |
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| Authors: | YU Xue-jing MA Xiao-fei XIA Bin |
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| Affiliation: | (1. College of Information Broadcast Engineering, Changchun Industry University, Changchun 130012; 2. 94580 Army, Bengbu 233000) |
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| Abstract: | Aiming at the problem that normal Particle Swarm Optimization(PSO) algorithm can not approach the best position effectively in dynamic environment,this paper proposes a dynamic PSO algorithm. It sets sensing particle and response threshold. When sensing particle's fitness change exceeds response threshold,the algorithm reinitializes the swarm and particle velocity. It designs double-hump DF1 dynamic model to validate the capability of this algorithm. Simulation experimental results show that it has high abi... |
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| Keywords: | Particle Swarm Optimization(PSO) algorithm dynamic double-hump DF1 model sensitive particle |
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