Abstract
Unlike many GAs, the Parameter-less Population Pyramid (P3) is an optimization model that avoids premature convergence due to the pyramid-like structure of populations, and thus P3 can be applied to a wide range of problems without parameter tuning. However, in some problems, P3 cannot control the number of fitness evaluations in local search and in crossover, while adapting problem structures. Meanwhile, we have proposed a novel technique, called DII analysis. The computational complexity of applied problems can be estimated based on the number of local optima according to the results obtained using DII. In order to solve the problem of P3, we also have proposed combining P3 with DII analysis (P3-DII). In this study, we investigated the effect of DII analysis on balance between genetic operators. The performance of P3-DII was confirmed according to the computational experiments which were carried out taking several combinational problems as examples.
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Acknowledgments
A part of this work was supported by JSPS KAKENHI Grant, Grant-in-Aid for Scientific Research(C), 26330282, by JSPS KAKENHI Grant, Grant-in-Aid for JSPS Fellows, 16J10941, and by Program for Leading Graduate Schools of Ministry of Education, Culture, Sports, Science and Technology in Japan.
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Hasegawa, T., Araki, Y., Mori, N., Matsumoto, K. (2017). Analysis of Parameter-Less Population Pyramid on the Local Distribution of Inferior Individuals. In: Leu, G., Singh, H., Elsayed, S. (eds) Intelligent and Evolutionary Systems. Proceedings in Adaptation, Learning and Optimization, vol 8. Springer, Cham. https://doi.org/10.1007/978-3-319-49049-6_11
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DOI: https://doi.org/10.1007/978-3-319-49049-6_11
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