| 对传统遗传算法的两处改进 |
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| 引用本文： | 张立君,范建华,张云龙.对传统遗传算法的两处改进[J].河南科学,2007,25(1):104-106. |
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| 作者姓名： | 张立君 范建华 张云龙 |
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| 作者单位： | 商丘职业技术学院,计算机系,河南,商丘,476000;空军第一航空学院,基础部,河南,信阳,464000 |
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| 摘 要： | 比照传统遗传算法与生物界进化过程,分析了引起传统遗传算法收敛速度慢和寻优效率低的两个原因.有针对性地对传统遗传算法进行了两处改进:一是加强了进化过程中环境选择压力变化和种群数量变化的共同作用,以便使得优秀基因在种群中迅速占统治地位;二是对优秀基因采取必要的保护措施,使得优秀基因的稳定性得到了保证.仿真结果验证了这种改进方法的有效性。
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| 关 键 词： | 遗传算法 收敛速度 寻优效率 生物界进化 |
| 文章编号： | 1004-3918（2007）01-0104-03 |
| 修稿时间： | 2006-09-08 |
Two Improvements for the Traditional Genetic Algorithms |
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| ZHANG Li-jun,FAN Jian-hua,ZHANG Yun-long.Two Improvements for the Traditional Genetic Algorithms[J].Henan Science,2007,25(1):104-106. |
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| Authors: | ZHANG Li-jun FAN Jian-hua ZHANG Yun-long |
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| Institution: | 1, Computer Department, Shangqiu Vocational and Technical College, Shangqiu, 476000, China; 2. Fundamental Department, The First Aaronautical Institute of Air Force, Xinyang, 464000, China |
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| Abstract: | By contrasting the traditional genetic algorithms(TGA)with the biologic evolution,two kinds of reasons that the convergence speed and searching efficiency in TGA are both lower are concluded.So we can improve the TGA process in two places: One is enhancing the co-effect of the variations environment selective pressure and population amount,so as to let the fit individuals can quickly become dominant in population.The other is protecting the fit individuals properly,so as to guarantee their stabilization.The simulation results show that this kind of improvement method is effective. |
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| Keywords: | genetic algorithm convergence speed searching efficiency biologic evolution |
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