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Using problem generators to explore the effects of epistasis
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Morgan Kaufmann
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Fitness landscapes: NK landscapes
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Institute of Physics Publishing & Oxford Univ. Press
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Epistasis variance: A viewpoint of GA-hardness
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Morgan Kaufmann
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Y. Davidor, "Epistasis variance: A viewpoint of GA-hardness," Foundations of Genetic Algorithms, pp.23-35, Morgan Kaufmann, 1991.
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Davidor, Y.1
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The genetic algorithm and the structure of the fitness landscape
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Morgan Kaufmann
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Evolving better representations through selective genome growth
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IEEE, Pistcaway, NJ
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Test function generators as embedded landscapes
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Morgan Kaufmann
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R. Heckendorn, S. Rana, and D. Whitley, "Test function generators as embedded landscapes," Foundations of Genetic Algorithms 5, pp.183-198, Morgan Kaufmann, 1999.
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Niches in NK-landscapes
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Morgan Kaufmann
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K.E. Mathias, L.J. Eshelman, and D. Schaffer, "Niches in NK-landscapes," Foundations of Genetic Algorithms 6, pp.27-46, Morgan Kaufmann, 2001.
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Mutation strategy improves GA's performance on epistatic problems
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M. Shinkai, H. Aguirre, and K. Tanaka, "Mutation strategy improves GA's performance on epistatic problems," Proc. 2002 IEEE World Congress on Computational Intelligence, pp.795-800, 2002.
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The CHC adaptive search algorithm: How to have a save search when engaging in nontraditional genetic recombination
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Morgan Kaufmann
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L.J. Eshelman, "The CHC adaptive search algorithm: How to have a save search when engaging in nontraditional genetic recombination," Foundations of Genetic Algorithms, pp.265-283, Morgan Kaufmann, 1991.
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Eshelman, L.J.1
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Bit-climbing, representational bias, and test suite design
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Morgan Kaufmann
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L. Davis, "Bit-climbing, representational bias, and test suite design," Proc. 4th Int'l Conf. on Genetic Algorithms, pp.18-23, Morgan Kaufmann, 1991.
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Davis, L.1
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An examination of tunable, random search landscapes
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Morgan Kaufmann
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R.E. Smith and J.E. Smith, "An examination of tunable, random search landscapes," Foundations of Genetic Algorithms 5, pp.165-182, Morgan Kaufmann, 1999.
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Morgan Kaufmann
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R.E. Smith and J.E. Smith, "New methods for tunable, random landscapes," Foundations of Genetic Algorithms 6, pp.47-67, Morgan Kaufmann, 2001.
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Cooperative model for genetic operators to improve GAs
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H. Aguirre, K. Tanaka, and T. Sugimura, "Cooperative model for genetic operators to improve GAs," Proc. IEEE Int'l Conf. on Information, Intelligence, and Systems, pp.98-106, 1999.
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Cooperative-competitive model for genetic operators: Contributions of extinctive selection and parallel genetic operators
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Morgan Kaufmann
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H. Aguirre, K. Tanaka, T. Sugimura, and S. Oshita, "Cooperative-competitive model for genetic operators: Contributions of extinctive selection and parallel genetic operators," Proc. Late Breaking Papers Genetic and Evolutionary Computation Conference, pp.6-14, Morgan Kaufmann, 2000.
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19
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The GENITOR algorithm and selection pressure: Why rank-based allocation of reproductive trials is best
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Morgan Kaufmann
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Preventing premature convergence in genetic algorithms by preventing incest
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Morgan Kaufmann
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The effect of incest prevention on genetic drift
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Morgan Kaufmann
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D. Schaffer, M. Mani, L. Eshelman, and K. Mathias, "The effect of incest prevention on genetic drift," Foundations of Genetic Algorithms 5, pp.235-243, Morgan Kaufmann, 1999.
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Solving cutting stock problems by evolutionary programming
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Evolutionary Programming VII: Proc. Seventh Annual Conference on Evolutionary Programming (EP98), Springer-Verlag
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From an individual to a population: An analysis of the first hitting time of population-based evolutionary algorithms
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J. He and X. Yao, "From an individual to a population: An analysis of the first hitting time of population-based evolutionary algorithms," IEEE Trans. Evol. Comput., vol.6, no.5, pp.495-511, 2002.
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