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| Adaptive Clonal Selection Algorithm and Its Simulation |
| WEI Yuan-Yuan1,2, TANG Chao-Li3 , HUANG You-Rui3 |
1.Research Center of Intelligent Information System, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031
2.School of Information Science and Technology, University of Science and Technology of China, Hefei 230027
3.School of Electrical Engineering, Anhui University of Science and Technology, Huainan 232001 |
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Abstract Based on the basic principle of clonal selection algorithm, an adaptive clonal selection algorithm (ACSA) for function optimization is proposed. The clone number of antibody, the high frequency mutation ratios and the renewal number of each generation can regulate automatically in ACSA. Meanwhile, mutation antibodies have the ability of immune memory. The results indicate that the ACSA has stronger convergence and adaptability through the convergence analysis and simulation compared with standard clonal selection algorithm.
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Received: 26 April 2007
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2009, Vol. 22 
