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.
| 源语言 | 英语 |
|---|---|
| 页(从-至) | 91-98 |
| 页数 | 8 |
| 期刊 | Lecture Notes in Computer Science |
| 卷 | 3512 |
| DOI | |
| 出版状态 | 已出版 - 2005 |
| 已对外发布 | 是 |
| 活动 | 8th International Workshop on Artificial Neural Networks, IWANN 2005: Computational Intelligence and Bioinspired Systems - Vilanova i la Geltru, 西班牙 期限: 8 6月 2005 → 10 6月 2005 |
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