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A Hybrid Hyper-Mutation Immune Clone Algorithm Based on Antibodies Cluster |
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PP: 433S-438S |
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Author(s) |
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Xu Xuesong,
Liu Xinbao,
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Abstract |
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Based on the inspiration of immune system, a new multi-objective optimization algorithm is presented. The proposed approach adopts a cluster mechanism in order to divide the antibodies into subpopulations for the stage of selection and reproduction. In the immune clone selection process, a hybrid hyper-mutation operator is introduced to improve the variety of antibodies and affinity maturation, thus it can quickly obtain the global and local optima. The convergence and time complexity of the algorithm is analyzed in this paper. The multi-objective optimization simulation results illustrated that the efficiency of the proposed algorithm and verified it’s remarkable quality of the global and local convergence reliability. |
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