Abstract
A novel quantum evolutionary algorithm based on immune operator (MQEA) is proposed. The algorithm can find out optimal solution by the mechanism in which antibody can be clone selected, immune cell can accomplish cross-mutation and Self-adaptive mutation, memory cells can be produced and similar antibodies can be suppressed. It not only can maintain quite nicely the population diversity than the classical evolutionary algorithm, but also can help to accelerate the convergence speed. The technique for improving the performance of MQEA has been described and its superiority is shown by some simulation experiments in this paper. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Xiaoming, Y., Sheng, L., & Dianxun, S. (2007). Studying the performance of quantum evolutionary algorithm based on immune theory. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4490 LNCS, pp. 1068–1075). https://doi.org/10.1007/978-3-540-72590-9_161
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