| 一种免疫遗传算法研究及应用 |
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| 引用本文： | 张礼兵,金菊良,王军.一种免疫遗传算法研究及应用[J].合肥工业大学学报(自然科学版),2004,27(7):734-737. |
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| 作者姓名： | 张礼兵 金菊良 王军 |
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| 作者单位： | 合肥工业大学,土木与建筑工程学院,安徽,合肥,230009 |
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| 基金项目： | 国家自然科学基金重大资助项目(50099620)，安徽省自然科学基金资助项目(01045102)，教育部优秀青年教师资助计划([2002]350)，安徽省优秀青年科技基金资助项目(2001) |
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| 摘 要： | 为克服标准遗传算法(SGA)搜索效率低、收敛速度慢等缺陷,文章提出了一种免疫遗传算法(IGA),即在父代优秀个体群的基础上叠加一个服从正态分布的随机变量来产生子代个体,以此综合体现父代优秀个体的遗传性和免疫性。研究表明,IGA对SGA的改进是有效且可行的,显示出稳健的全局优化、计算量少和求解精度高等特点,具有较高的应用价值。
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| 关 键 词： | 遗传算法 免疫算法 正态分布 |
| 文章编号： | 1003-5060(2004)07-0734-04 |
| 修稿时间： | 2003年9月4日 |
Study of an immune genetic algorithm and its application |
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| ZHANG Li-bing,JIN Ju-liang,WANG Jun.Study of an immune genetic algorithm and its application[J].Journal of Hefei University of Technology(Natural Science),2004,27(7):734-737. |
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| Authors: | ZHANG Li-bing JIN Ju-liang WANG Jun |
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| Abstract: | In order to improve the poor efficiency and stability of the simple genetic algorithm(SGA),an immune genetic algorithm(IGA) is studied in this paper. A random variable with normal distribution is added into the excellent forerunner individuals to produce the new generation so as to incarnate both transmissibility and immunity of the forerunner individuals. The results of two examples show that the improvement on the SGA is marked by using the IGA,and the presented IGA has the attributes of steady overall optimization,less calculation and high precision,and it can be applied to solve most of complex optimization problems. |
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| Keywords: | genetic algorithm immune algorithm normal distribution |
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