Abstract
An interactive genetic algorithm with evaluating individuals using variational granularity was presented in this study to effectively alleviate user fatigue. In this algorithm, multiple language sets with different evaluation granularities are provided. The diversity of a population described with the entropy of its gene meaning units is utilized to first choose parts of appropriate language sets to participate in evaluating the population. A specific language set for evaluating an individual is further selected from these sets according to the distance between the individual and the current preferred one. The proposed algorithm was applied to a curtain evolutionary design system and compared with previous typical ones. The empirical results demonstrate the strengths of the proposed algorithm in both alleviating user fatigue and improving the efficiency in search.
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Gong, D., Chen, J., Sun, X., Zhang, Y. (2012). Application of Variational Granularity Language Sets in Interactive Genetic Algorithms. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7665. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34487-9_10
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DOI: https://doi.org/10.1007/978-3-642-34487-9_10
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