@inproceedings{909e4bf731b949058fd0afd75d8ffaef,
title = "Lamarckian clonal selection algorithm with application",
abstract = "In this paper, Lamarckism and Immune Clonal Selection Theory are integrated to form a new algorithm, Lamarckian Clonal Selection Algorithm (LCSA). 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). In the experiments, ten benchmark functions are used to test the performance of LCSA, and the impact of parameters for LCSA is studied with great care. Compared with SCSA and the relevant evolutionary algorithm, LCSA is more robust and has better convergence.",
author = "Wuhong He and Haifeng Du and Licheng Jiao and Jing Li",
year = "2005",
doi = "10.1007/11550822\_50",
language = "英语",
isbn = "3540287523",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "317--322",
booktitle = "Artificial Neural Networks",
note = "15th International Conference on Artificial Neural Networks: Biological Inspirations, ICANN 2005 ; Conference date: 11-09-2005 Through 15-09-2005",
}