Abstract
Combining the clonal selection mechanism of the immune system with the evolution equations of particle swarm optimization, an advanced algorithm was introduced for functions optimization. The advantages of this algorithm lies in two aspects. Via immunity operation, the diversity of the antibodies was maintained, and the speed of convergent was improved by using particle swarm evolution equations. Simulation programme and three functions were used to check the effect of the algorithm. The advanced algorithm were compared with clonal selection algorithm and particle swarm algorithm. The results show that this advanced algorithm can converge to the global optimum at a great rate in a given range, the performance of optimization is improved effectively.
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Foundation item: Project(A1420060159) supported by the National Basic Research of China; projects(60234030, 60404021) supported by the National Natural Science Foundation of China
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Liu, Lj., Cai, Zx. & Chen, H. Immunity clone algorithm with particle swarm evolution. J Cent. South Univ. Technol. 13, 703–706 (2006). https://doi.org/10.1007/s11771-006-0017-5
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DOI: https://doi.org/10.1007/s11771-006-0017-5