Lamarckian clonal selection algorithm based function optimization

被引:0
|
作者
He, WH [1 ]
Du, HF
Jiao, LC
Li, J
机构
[1] Xidian Univ, Inst Intelligent Informat Proc, Xian 710071, Peoples R China
[2] Xidian Univ, Natl Key Lab Radar Signal Proc, Xian 710071, Peoples R China
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Based on Lamarckism and Immune Clonal Selection Theory, Lamarckian Clonal Selection Algorithm (LCSA) is proposed in this paper. In the novel algorithm, the idea that Lamarckian evolution described how organism can evolve through learning, namely the point of "Gain and Convey" is applied, then this kind of learning mechanism is introduced into Standard Clonal Selection Algorithm (SCSA). Through the experimental results of optimizing complex multimodal functions, compared with SCSA and the relevant evolutionary algorithm, LCSA is more robust and has better convergence.
引用
收藏
页码:91 / 98
页数:8
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