[1]杨丽娜,刘刚,王秋生..一种改进的遗传算法及其应用[J].郑州大学学报(工学版),2005,26(03):98-101.[doi:10.3969/j.issn.1671-6833.2005.03.026]
 Yang Lina,LIU Gang,Wang Qiusheng.An improved genetic algorithm and its application[J].Journal of Zhengzhou University (Engineering Science),2005,26(03):98-101.[doi:10.3969/j.issn.1671-6833.2005.03.026]
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一种改进的遗传算法及其应用()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
26
期数:
2005年03期
页码:
98-101
栏目:
出版日期:
1900-01-01

文章信息/Info

Title:
An improved genetic algorithm and its application
作者:
杨丽娜刘刚王秋生.
解放军信息工程大学电子技术学院,河南,郑州,450004, 北京科技大学信息工程学院,北京,100083
Author(s):
Yang Lina; LIU Gang; Wang Qiusheng
关键词:
遗传算法 容错系统 优化模型
Keywords:
DOI:
10.3969/j.issn.1671-6833.2005.03.026
文献标志码:
A
摘要:
遗传算法由于其隐合并行性和全局搜索特性,使其具有其他常规优化算法无法拥有的优点.然而,标准遗传算法存在着收敛速度慢、易"早熟"等缺陷.针对应用标准遗传算法时所存在的局限性,从适应值、交叉和变异算子以及控制参数的选取等多方面进行了遗传算法的改进设计.这种改进的遗传算法可进一步改善算法的搜索能力、搜索效率和收敛性能.最后以(N+M)客错系统的优化模型作为优化目标,得到了费用模型的最优解.计算结果验证了算法的有效性和正确性.
Abstract:
Due to its hidden row and global search characteristics, the genetic algorithm has advantages that other conventional optimization algorithms cannot have. However, the standard genetic algorithm has shortcomings such as slow convergence speed and easy "precocious puberty". In view of the limitations of the standard genetic algorithm, the design of the genetic algorithm is improved from many aspects, such as adaptation value, crossover and variation operators, and selection of control parameters. This improved genetic algorithm can further improve the search ability, search efficiency and convergence performance of the algorithm. Finally, the optimization model of (N+M) customer-error system is taken as the optimization goal, and the optimal solution of the cost model is obtained. The calculation results verify the validity and correctness of the algorithm.

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更新日期/Last Update: 1900-01-01