| 云遗传算法 |
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| 引用本文： | 戴朝华,朱云芳,陈维荣.云遗传算法[J].西南交通大学学报,2006,41(6):729-732. |
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| 作者姓名： | 戴朝华 朱云芳 陈维荣 |
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| 作者单位： | 1. 西南交通大学电气化自动化研究所,四川,成都,610031
2. 西南交通大学峨眉校区,四川,峨眉山,614202 |
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| 摘 要： | 为了克服传统遗传算法搜索速度慢、易陷入局部最优解的缺陷，借鉴遗传算法的思想，利用云模型云滴的随机性和稳定倾向性的特点，提出了一种新的遗传算法——云遗传算法（CGA）．该算法由正态云模型的Y条件云发生器实现交叉操作，由基本云发生器实现变异操作．最后，进行了函数优化实验，并与标准遗传算法（SGA）和自适应遗传算法（AGA）进行了比较，以证明其有效性．
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| 关 键 词： | 遗传算法 云理论 云遗传算法 函数优化 |
| 文章编号： | 0258-2724（2006）06-0729-04 |
| 收稿时间： | 2005-09-28 |
| 修稿时间： | 2005-09-28 |
Cloud Theory-Based Genetic Algorithm |
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| DAI Chaohua,ZHU Yunfang,CHEN Weirong.Cloud Theory-Based Genetic Algorithm[J].Journal of Southwest Jiaotong University,2006,41(6):729-732. |
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| Authors: | DAI Chaohua ZHU Yunfang CHEN Weirong |
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| Abstract: | To overcome the shortcomings of a genetic algorithm(GA).i.e.,low convergence speed and easily getting a local optimum solution,a novel genetic algorithm,cloud theory-based genetic algorithm(CGA),was proposed.CGA is based on both the idea of GA and the properties of randomness and stable tendency of a normal cloud model.In this algorithm,Y-conditional cloud generator is used as the cross operator,and basic cloud generator as the mutation operator.Finally,an experiment of function optimization was carried out and a comparison with standard genetic algorithm(SGA) and adaptive genetic algorithm(AGA) was made to testify the validity of CGA,the proposed genetic algorithm. |
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| Keywords: | genetic algorithm cloud theory cloud genetic algorithm function optimization |
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