[1]阎昌琪,刘成洋,王建军.新型混合粒子群算法在核动力设备优化设计中的应用[J].哈尔滨工程大学学报,2012,(04):534-538.[doi:10.3969/j.issn.1006-7043.201105073]
 YAN Changqi,LIU Chengyang,WANG Jianjun.Application of a new hybrid particle swarm optimization in the optimal design of nuclear power components[J].Journal of Harbin Engineering University,2012,(04):534-538.[doi:10.3969/j.issn.1006-7043.201105073]
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新型混合粒子群算法在核动力设备优化设计中的应用(/HTML)
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2012年04期
页码:
534-538
栏目:
出版日期:
2012-04-25

文章信息/Info

Title:
Application of a new hybrid particle swarm optimization in the optimal design of nuclear power components
文章编号:
1006-7043(2012)04-0534-05
作者:
阎昌琪刘成洋王建军
哈尔滨工程大学 核科学与技术学院,黑龙江 哈尔滨 150001
Author(s):
YAN Changqi LIU Chengyang WANG Jianjun
College of Nuclear Science and Technology, Harbin Engineering University, Harbin 150001, China
关键词:
粒子群算法复合形算法遗传算法核动力设备优化设计
分类号:
TL353
DOI:
10.3969/j.issn.1006-7043.201105073
文献标志码:
A
摘要:
针对标准粒子群算法在处理非线性约束优化问题时存在收敛速度慢、精度低和易陷入局部最优的缺点,设计了一种新型混合粒子群算法,该算法采用可行性原则处理约束条件,避免惩罚函数法中惩罚因子选取的困难;引入基本复合形法产生初始可行群体,加快粒子群收敛速度;引入遗传算法的交叉和变异策略,避免粒子群陷入局部最优;在迭代末期的优解附近,进行改进复合形算法的寻优,提高最优解的精度.通过算法测试基准函数的优化计算,结果显示,新型混合粒子群算法有较好的优化性能,并在核动力设备优化设计中有很好的应用.

参考文献/References:

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更新日期/Last Update: 2012-06-05