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Software for Continuous Global Optimization Using Unix C++

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Bayesian Heuristic Approach to Discrete and Global Optimization

Part of the book series: Nonconvex Optimization and Its Applications ((NOIA,volume 17))

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Abstract

The set of optimization algorithms and the rules how to use them are similar to that of the Fortran library, but not the same. Therefore we will present a short description of these algorithms in this chapter.

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Authors and Affiliations

  1. Institute of Mathematics and Informatics, Kaunas Technological University, Vilnius, Lithuania

    Jonas Mockus

  2. Vytautas Magnus University, Vilnius, Lithuania

    Jonas Mockus

  3. Vilnius Technical University, Vilnius, Lithuania

    Jonas Mockus

  4. Department of Statistics, Carnegie-Mellon University, Pittsburgh, Pennsylvania, USA

    William Eddy

  5. Lucent Technologies AT&T Bell Laboratories, Pittsburgh, Pennsylvania, USA

    Audris Mockus

  6. School of Chemical Engineering, Purdue University, W. Lafayette, Indiana, USA

    Linas Mockus & Gintaras Reklaitis

Authors
  1. Jonas Mockus
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  2. William Eddy
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  3. Audris Mockus
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  4. Linas Mockus
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  5. Gintaras Reklaitis
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© 1997 Springer Science+Business Media Dordrecht

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Mockus, J., Eddy, W., Mockus, A., Mockus, L., Reklaitis, G. (1997). Software for Continuous Global Optimization Using Unix C++. In: Bayesian Heuristic Approach to Discrete and Global Optimization. Nonconvex Optimization and Its Applications, vol 17. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2627-5_19

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  • DOI: https://doi.org/10.1007/978-1-4757-2627-5_19

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-4767-3

  • Online ISBN: 978-1-4757-2627-5

  • eBook Packages: Springer Book Archive

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