Abstract
In this paper, some guidelines for setting the parameters of quantum-inspired evolutionary algorithm (QEA) are presented. Although the performance of QEA is excellent, there is relatively little or no research on the effects of different settings for its parameters. The guidelines are drawn up based on extensive experiments.
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References
Han, K.-H., Kim, J.-H.: Quantum-inspired Evolutionary Algorithm for a Class of Combinatorial Optimization. IEEE Trans. Evol. Comput. 6 (2002) 580–593
Kim, K.-H., Hwang, J.-Y., Han, K.-H., Kim, J.-H., Park, K.-H.: A Quantum-inspired Evolutionary Computing Algorithm for Disk Allocation Method. IEICE Trans. Inf. & Syst., E86-D (2003) 645–649
Jang, J.-S., Han, K.-H., Kim, J.-H.: Quantum-inspired Evolutionary Algorithm-based Face Verification. Proc. Genet. & Evol. Comput. Conf. (2003)
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Han, KH., Kim, JH. (2003). On Setting the Parameters of QEA for Practical Applications: Some Guidelines Based on Empirical Evidence. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2723. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45105-6_52
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DOI: https://doi.org/10.1007/3-540-45105-6_52
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