Abstract
This paper proposes a new 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 individual, the evaluation function, and the population dynamics. QICA uses a quantum bit, defined as the smallest unit of information, for the probabilistic representation and a quantum bit individual as a string of quantum bits. In QICA, by quantum mutation operator, we can make full use of the information of the current best individual to perform the next search for speeding up the convergence. Information among the subpopulation is exchanged by adopting the quantum crossover operator for improvement of diversity of the population and avoiding prematurity. We execute the proposed algorithm to solve the benchmark problems with 30,100 and 2000 dimensions and very large numbers of local minima. The result shows that the proposed algorithm can close-to-optimal solution by the less computational cost.
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References
De Castro, L.N., Timmis, J.: Artificial Immune Systems: A New Computational Intelligence Approach. Springer, London (1996)
Dasgupta, D.: Artificial Immune Systems and Their Applications. Springer, Berlin (1999)
Hofmeyr, S.A., Forrest, S.: Immunity by design: An artificial immune system. In: Proc. Genetic and Evolutionary Computation Conf., July 1999, pp. 1289–1296 (1999)
De Castro, L.N., Von Zuben, F.J.: Artificial Immune Systems: Part I—Basic Theory and Applications. FEEC/Univ. Campinas, Campinas, Brazil (Online) (1999), Available http://www.dca.fee.unicamp.br/~lnunes/immune.html
De Castro, L.N., Von Zuben, F.J.: Artificial Immune Systems: Part II—A Survey of Applications. FEEC/Univ. Campinas, Campinas, Brazil (Online) (2000), Available http://www.dca.fee.unicamp.br/lnunes/immune.html
Leung, Y.W., Wang, Y.P.: An Orthogonal Genetic Algorithm with Quantization for Global Numerical Optimization. IEEE Transactions on Evolutionary Computation 5(1), 41–53 (2001)
Heinz, M., Dirk, S.V.: Predictive Models for the Breeder Genetic Algorithm. Evolutionary Computation 1(1), 25–49 (1993)
Davis, T.E., Principe, J.C.: A simulated annealing like convergence theory for the simple genetic algorithm. In: Belew, R.K., Booker, L.B. (eds.) Proc. 4th Conf. Gentic Algorithms, San Mateo, CA (1991)
Hey, T.: Quantum computing: An introduction. Computing & Control Engineering Journal 10(3), 105–112 (1999)
Grover, L.K.: A framework for fast quantum mechanical algorithms. In: Proceeding of the 30th Annual ACM Symposium on Theory of Computing, pp. 53–62. ACM Press, New York (1998)
Altaisky, M.V.: Quantum neutral network, arXiv: quant-ph/0107012 v2 5 (July 2001)
Yao, A.: Quantum circuit complexity. In: Proceedings of the 34th IEEE symposium on Foundations of computer science, pp. 352–361 (1993)
Aharonov, D., Kitaev, A., Nisan, N.: Quantum circuits with mixed states, LANL e-print quant-ph/ 9806029 (1998)
Burnet, F.M.: Clonal Selection and After. In: Bell, G.I., Perelson, A.S., Pimbley Jr., G.H. (eds.) Theoretical Immunology, pp. 63–85. Marcel Dekker Inc., New York (1978)
Narayanna, A., Moore, M.: Quantum-inspired genetic algorithms. In: Proceedings of IEEE International Conference on Evolutional Evolution, pp. 61–66 (1996)
Liu, R.C., Du, H.F., Jiao, L.C.: Immunity Poly-Clonal Strategies. Journal of Computer Research and Development 41(4), 571–576 (2004)
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Li, Y., Jiao, L. (2005). Quantum-Inspired Immune Clonal Algorithm. In: Jacob, C., Pilat, M.L., Bentley, P.J., Timmis, J.I. (eds) Artificial Immune Systems. ICARIS 2005. Lecture Notes in Computer Science, vol 3627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11536444_23
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DOI: https://doi.org/10.1007/11536444_23
Publisher Name: Springer, Berlin, Heidelberg
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