[1]李国庆,尹洪胜.采用遗传算法的网络优化技术[J].华侨大学学报(自然科学版),2015,36(6):663-666.[doi:10.11830/ISSN.1000-5013.2015.06.0663]
　LI Guoqing,YIN Hongsheng.Network Optimization Technique Using Genetic Algorithm[J].Journal of Huaqiao University(Natural Science),2015,36(6):663-666.[doi:10.11830/ISSN.1000-5013.2015.06.0663]
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采用遗传算法的网络优化技术()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第36卷
期数:
2015年第6期
页码:
663-666
栏目:
出版日期:
2015-11-10

文章信息/Info

Title:
Network Optimization Technique Using Genetic Algorithm
文章编号:
1000-5013(2015)06-0663-04
作者:
李国庆;  尹洪胜
中国矿业大学 信息与电气工程学院, 江苏 徐州 221008
Author(s):
LI Guoqing;  YIN Hongsheng
School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, China
关键词:
树型网络;  网络优化;  遗传算法;  适应度函数
Keywords:
tree-shape network;  network optimization;  genetic algorithm;  fitness function
分类号:
TP312;TP393
DOI:
10.11830/ISSN.1000-5013.2015.06.0663
文献标志码:
A
摘要:
针对树型网络的拓扑结构和数学模型,从个体编码、种群初始化、种群进化、适应度函数等方面构建基于遗传算法的网络优化方法.实验结果表明:所构建的方法进一步修正了适应度函数,增强了弱势个体被选择的概率,避免遗传算法优化过程的过早收敛问题,缩短了执行时间,取得了较佳的网络优化结果.
Abstract:
Based on genetic algorithm, a network optimization method is proposed according to the topology and mathematical model of tree-shape network from the aspects of individual encoding, population initialization, population evolution, fitness function and so on. Experimental results show that the proposed method can further modify the fitness function, enhance the probability of the weak individuals’ being chosen, avoid the premature convergence of genetic algorithm, and reduce the execution time. The results show good networking optimization.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2015-10-08
通信作者: 李国庆(1966-),男,副教授,主要从事软件工程、计算机网络应用技术的研究.E-mail:xzcxlgq@126.com.
基金项目: 国家自然科学基金资助项目(61379100)
更新日期/Last Update: 2015-11-20