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Constructing large feasible suboptimal intervals for constrained nonlinear optimization

  • Global Optimization
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Abstract

An algorithm for finding a large feasiblen-dimensional interval for constrained global optimization is presented. Then-dimensional interval is iteratively enlarged about a seed point while maintaining feasibility. An interval subdivision method may be used to check feasibility of the growing box. The resultant feasible interval is constrained to lie within a given level set, thus ensuring it is close to the optimum. The ability to determine such a feasible interval is useful for exploring the neighbourhood of the optimum, and can be practically used in manufacturing considerations. The numerical properties of the algorithm are tested and demonstrated by an example problem.

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Authors and Affiliations

  1. Kalmár Laboratory, József Attila University, Szeged, Hungary

    Tibor Csendes

  2. Industrial Engineering Program, University of Washington, Seattle, WA, USA

    Zelda B. Zabinsky & Birna P. Kristinsdottir

Authors
  1. Tibor Csendes
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  2. Zelda B. Zabinsky
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  3. Birna P. Kristinsdottir
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Additional information

This work was supported by Grants OTKA 2879/1991 and OTKA 2675/1991, and in part by NSF Grant DDM-9211001.

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Csendes, T., Zabinsky, Z.B. & Kristinsdottir, B.P. Constructing large feasible suboptimal intervals for constrained nonlinear optimization. Ann Oper Res 58, 279–293 (1995). https://doi.org/10.1007/BF02096403

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  • DOI: https://doi.org/10.1007/BF02096403

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