Abstract
This paper proposes a novel immune clonal algorithm, called a quantum-inspired immune clonal algorithm (QICA), which is based on the concept and principles of quantum computing, such as a quantum bit and superposition of states. Like other evolutionary algorithms, QICA is also characterized by the representation of the antibody (individual), the evaluation function, and the population dynamics. However, in QICA, antibody is proliferated and divided into a set of subpopulation groups. Antibodies in a subpopulation group are represented by multi-state gene quantum bits. In the antibody’s updating, the scabilitable quantum rotation gate strategy and dynamic adjusting angle mechanism are applied to guide searching. Theoretical analysis has proved that QICA converges to the global optimum. Some simulations are given to illustrate its efficiency and better performance than its counterpart.
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Li, Y., Liu, F. (2006). A Novel Immune Clonal Algorithm. In: Jiao, L., Wang, L., Gao, X., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4222. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881223_4
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DOI: https://doi.org/10.1007/11881223_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45907-1
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