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Test Results for an Interval Branch and Bound Algorithm for Equality-Constrained Optimization

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State of the Art in Global Optimization

Part of the book series: Nonconvex Optimization and Its Applications ((NOIA,volume 7))

Abstract

Various techniques have been proposed for incorporating constraints in interval branch and bound algorithms for global optimization. However, few reports of practical experience with these techniques have appeared to date. Such experimental results appear here. The underlying implementation includes use of an approximate optimizer combined with a careful tesselation process and rigorous verification of feasibility. The experiments include comparison of methods of handling bound constraints and comparison of two methods for normalizing Lagrange multipliers. Selected test problems from the Floudas / Pardalos monograph are used, as well as selected unconstrained test problems appearing in reports of interval branch and bound methods for unconstrained global optimization.

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Author information

Authors and Affiliations

  1. Department of Mathematics, University of Southwestern Louisiana, U.S.L. Box 4-1010, Lafayette, Louisiana, 70504-1010, USA

    R. Baker Kearfott

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  1. R. Baker Kearfott
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Editor information

Editors and Affiliations

  1. Princeton University, USA

    C. A. Floudas

  2. University of Florida, USA

    P. M. Pardalos

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© 1996 Kluwer Academic Publishers

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Kearfott, R.B. (1996). Test Results for an Interval Branch and Bound Algorithm for Equality-Constrained Optimization. In: Floudas, C.A., Pardalos, P.M. (eds) State of the Art in Global Optimization. Nonconvex Optimization and Its Applications, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-3437-8_12

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  • DOI: https://doi.org/10.1007/978-1-4613-3437-8_12

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-3439-2

  • Online ISBN: 978-1-4613-3437-8

  • eBook Packages: Springer Book Archive

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