| 引用本文: | 郭忠全,王振国,颜力.基于种群分类的变尺度免疫克隆选择算法.[J].国防科技大学学报,2011,33(5):36-40.[点击复制] |
| GUO Zhongquan,WANG Zhenguo,YAN Li.Mutative Scale Immune Clonal Selection Algorithm Based on Multi-population[J].Journal of National University of Defense Technology,2011,33(5):36-40[点击复制] |
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| 基于种群分类的变尺度免疫克隆选择算法 |
| 郭忠全, 王振国, 颜力 |
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(国防科技大学 航天与材料工程学院，湖南 长沙 410073)
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| 摘要: |
| 提出了一种基于种群分类的变尺度免疫克隆选择算法。该算法通过对目标函数进行非线性尺度变换，突出了全局最优解的优势地位；建立记忆子群实现了种群代际进化信息的交换；依据亲和度将抗体分为精英子群、普通子群、劣等子群，并对其分别执行自适应高斯变异、均匀变异和消亡更新等策略，增强了算法的局部和全局搜索能力。引入小生境技术提高了抗体分布的多样性，进而克服了算法的早熟。采用经典测试函数和星载天线结构优化问题对算法进行了测试，测试结果表明本算法寻优能力较经典克隆选择算法和标准遗传算法有较大改善，且计算复杂度并无显著增加。 |
| 关键词: 人工免疫 克隆选择 种群分类 变尺度 星载天线优化 |
| DOI： |
| 投稿日期：2011-03-25 |
| 基金项目:国家自然科学基金资助项目（50975280，61004094）；教育部新世纪优秀人才支持计划资助项目（NCET-08-0149） |
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| Mutative Scale Immune Clonal Selection Algorithm Based on Multi-population |
| GUO Zhongquan, WANG Zhenguo, YAN Li |
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(College of Aerospace and Materials Engineering, National Univ. of Defense Technology, Changsha 410073, China)
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| Abstract: |
| Mutative Scale Immune Clonal Selection Algorithm (MSICSA) based on Multi-population is proposed. In the algorithm, the dominant position of global optimal solution was highlighted by the nonlinear scale transformation of objective function. Memory sub-population was extracted to exchange information between populations. Antibody population was divided into elite, normal and inferior sub-population. To enhance local and global search capabilities of MSICSA, adaptive Gaussian and uniform mutation were applied to elite and normal sub-population respectively and the inferior antibody was extinguished and replaced by new ones. By introducing the niche technology to increase the diversity of population distribution, the algorithm can prevent premature. Test functions and a space antenna optimization were tested. The results show that the optimization capability of MSICSA is more advanced than CLONALG and SGA, and the computational complexity is reduced. |
| Keywords: artificial immune clone selection multi-population mutative scale space antenna optimization |
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