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Interval arithmetic and genetic algorithms in global optimization

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Abstract

In this work we have combined two promising global optimization methods, interval arithmetic methods and genetic algorithms, into a set of hybrid algorithms that share the good properties of both methods while avoiding some drawbacks of the constituent methods. Interval aritmetic gives us some simple arithmetic methods to estimate the range of rational functions to be optimized, while genetic algorithms are able to adaptively guide the search.

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Authors and Affiliations

  1. Department of Information Technology and Industrial Management, University of Vaasa, P. O. Box 700, FIN-65101, Vaasa, Finland

    Jarmo T. Alander

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  1. Jarmo T. Alander
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© 1995 Springer-Verlag/Wien

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Alander, J.T. (1995). Interval arithmetic and genetic algorithms in global optimization. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_101

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  • DOI: https://doi.org/10.1007/978-3-7091-7535-4_101

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-82692-8

  • Online ISBN: 978-3-7091-7535-4

  • eBook Packages: Springer Book Archive

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