| 基于差分演化和克隆选择机制的优化算法 |
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| 引用本文： | 杨格兰,金辉霞,朱幸辉. 基于差分演化和克隆选择机制的优化算法[J]. 计算机工程与应用, 2013, 49(10): 50-52 |
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| 作者姓名： | 杨格兰 金辉霞 朱幸辉 |
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| 作者单位： | 1.湖南城市学院 计算机科学系，湖南 益阳 4130002.湖南城市学院 物理与电信工程系，湖南 益阳 4130003.湖南农业大学 信息科学工程学院，长沙 410128 |
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| 摘 要： | 为了解决函数优化过程中的“早熟收敛”和“搜索迟钝”问题，将差分演化算法与克隆选择算法进行了结合，提出了一种新的差分演化克隆选择算法。该算法将克隆选择操作引入到差分演化算法中，达到了既能够选出最好个体又能够保证种群多样性的效果。实验结果表明该算法在多峰值函数优化问题中，具有求解精度较高，收敛速度较快等优点。
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| 关 键 词： | 函数优化 早熟收敛 差分演化算法 克隆选择算法 |
Optimization algorithm based on differential evolution and clonal selection mechanism |
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| YANG Gelan,JIN Huixia,ZHU Xinghui. Optimization algorithm based on differential evolution and clonal selection mechanism[J]. Computer Engineering and Applications, 2013, 49(10): 50-52 |
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| Authors: | YANG Gelan JIN Huixia ZHU Xinghui |
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| Affiliation: | 1.Department of Computer Science, Hunan City University, Yiyang, Hunan 413000, China2.Department of Physics and Telecom Engineering, Hunan City University, Yiyang, Hunan 413000, China3.Institute of Information Engineering, Hunan Agricultural University, Changsha 410128, China |
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| Abstract: | To further avoid the problem of premature convergence and search stolidity in the process of resolving function optimization, a differential evolution clonal selection algorithm based on the clonal selection theory is proposed which can enhance the operating efficiency and the convergence rate of the differential evolution algorithm and then can both select the best individual and guarantee the population diversity. The simulation experimental results show that the result of the multiple hump function is accurate and the convergence speed is fast. |
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| Keywords: | numerical optimization premature convergence differential evolution clonal selection algorithm |
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