Abstract
A theoretical analysis of Michalewicz' non-uniform mutation operator is presented and a novel variant — the adaptive non-uniform mutation operator — is proposed. The non-uniform mutation operator was developed by Michalewicz' for his modified variant of genetic algorithms modGA to tackle numerical parameter optimization problems. As is shown by mathematical analysis, this mutation operator prefers parameter values in the center of the corresponding feasible region. This leads to problems if the optimum is situated near the feasible region's boundaries. In order to avoid this undesirable tendency, the adaptive non-uniform mutation operator is proposed, the development of which rests on the mathematical analysis. Experimental results for a standard numerical parameter optimization problem are given that illustrate the superiority and effectiveness of this novel mutation operator for genetic algorithms.
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References
Bäck, T.: Evolutionary Algorithms in Theory and Practice. New York: Oxford University Press, 1996
Baker, J.E.: Adaptive Selection Methods for Genetic Algorithms. In: Grefenstette, J.J. (Ed.): Proceedings of the First International Conference on Genetic Algorithms and Their Applications. Hillsdale: Lawrence Erlbaum Associates Publishers, pp. 101–111, 1985
Baker, J.E.: Reducing Bias and Inefficiency in the Selection Algorithm. In: Grefenstette, J.J. (Ed.): Genetic Algorithms and Their Applications: Proceedings of the Second International Conference on Genetic Algorithms. Hillsdale: Lawrence Erlbaum Associates Publishers, pp. 14–21, 1987
Baker, J.E.: An Analysis of the Effects of Selection in Genetic Algorithms. Ph.D., Vanderbilt University, 1989
Holland, J.H.: Adaptation in Natural and Artificial Systems: An Introductory-Analysis with Applications to Biology, Control, and Artificial Intelligence. Cambridge: First MIT Press Edition, 1992
Janikow, C.Z.; Michalewicz, Z.: An Experimental Comparison of Binary and Floating Point Representations in Genetic Algorithms. In: Belew, R.K.; Booker, L.B. (Eds.): Proceedings of the Fourth International Conference on Genetic Algorithms. San Mateo: Morgan Kaufmann Publishers, pp. 31–36, 1991
Michalewicz, Z.; Janikow, C.Z.: Handling Constraints in Genetic Algorithms. In: Belew, R.K.; Booker, L.B. (Eds.): Proceedings of the Fourth International Conference on Genetic Algorithms. San Mateo: Morgan Kaufmann Publishers, pp. 151–157, 1991
Michalewicz, Z.: Genetic Algorithms+Data Structures=Evolution Programs. Berlin: Springer-Verlag, 1992
Rechenberg, I.: Evolutionsstrategie '94. Werkstatt Bionik und Evolutionstechnik, Band 1, Stuttgart: frommann-holzboog, 1994
Schwefel, H.-P.: Evolution and Optimum Seeking. New York: John Wiley & Sons, 1995
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© 1997 Springer-Verlag Berlin Heidelberg
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Neubauer, A. (1997). Adaptive non-uniform mutation for genetic algorithms. In: Reusch, B. (eds) Computational Intelligence Theory and Applications. Fuzzy Days 1997. Lecture Notes in Computer Science, vol 1226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62868-1_94
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DOI: https://doi.org/10.1007/3-540-62868-1_94
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