Abstract
Mutation operators play an important role in evolutionary programming. Several different mutation operators have been developed in the past decades. However, each mutation operator is only efficient in some type of problems, but fails in another one. In order to overcome the disadvantage, a possible solution is to use a mixed mutation strategy, which mixes various mutation operators. In this paper, an example of such strategies is introduced which employs five different mutation strategies: Gaussian, Cauchy, Levy, single-point and chaos mutations. It also combines with the technique of species conservation to prevent the evolutionary programming from being trapped in local optima. This mixed strategy has been tested on 21 benchmark functions. The simulation results show that the mixed mutation strategy is superior to any pure mutation strategy.
This work is supported by National Natural Science Foundation of China under Grant (60443003).
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© 2005 Springer-Verlag Berlin Heidelberg
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Dong, H., He, J., Huang, H., Hou, W. (2005). A Mixed Mutation Strategy Evolutionary Programming Combined with Species Conservation Technique. In: Gelbukh, A., de Albornoz, Á., Terashima-Marín, H. (eds) MICAI 2005: Advances in Artificial Intelligence. MICAI 2005. Lecture Notes in Computer Science(), vol 3789. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11579427_60
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DOI: https://doi.org/10.1007/11579427_60
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