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An alternative Genetic Algorithm

  • Genetic Algorithms
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Parallel Problem Solving from Nature (PPSN 1990)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 496))

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Abstract

This paper presents a new Genetic Algorithm (GA), called Alternative Genetic Algorithm (AGA) which has been defined to facilitate theoretical investigations. We have shown that both AGA and the usual GA (UGA) obey similar difference equations. However, theoretical investigations on the AGA are much simpler than on the UGA. For the AGA, we can derive as a theoretical result the mean function value ‹f› in the population of individuals as a function of time. In an application of this result we show that the experimentally obtained ‹fA of the AGA approximates the ‹fU of the UGA within ≈ 1% when fitting the parameter representing the convergence speed, i.e., the mean increase of the mean function value in the population.

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References

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  3. C. L. Bridges; D. Goldberg. An Analysis of Reproduction and Crossover in a Binary-Coded Genetic Algorithm. Proc. 2nd Int'l Conf. Genetic Algorithms & Appl., Arlington, VA, pages 28–33, 1989.

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  4. G. Syswerda. Uniform Crossover in Genetic Algorithms. Proc. 3rd Int'l Conf. Genetic Algorithms & Appl., Arlington, VA, pages 2–9, 1989.

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Hans-Paul Schwefel Reinhard Männer

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© 1991 Springer-Verlag Berlin Heidelberg

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Hesser, J., Männer, R. (1991). An alternative Genetic Algorithm. In: Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature. PPSN 1990. Lecture Notes in Computer Science, vol 496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0029728

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  • DOI: https://doi.org/10.1007/BFb0029728

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54148-6

  • Online ISBN: 978-3-540-70652-6

  • eBook Packages: Springer Book Archive

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