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On a class of hybrid methods for smooth constrained optimization

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Abstract

With reference to smooth nonlinearly constrained optimization problems, we consider combinations of locally superlinearly convergent methods with globally convergent ones. The aim of this paper is threefold: to give a survey on well-known as well as possible unknown hybrid optimization methods, based on a special construction principle; to present a general convergence result for the class of hybrid algorithms; and to derive further methods for this class with new convergence properties.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Dresden University of Technology, Dresden, Germany

    H. Kleinmichel (Associate Professor) & K. Schönefeld (Assistant Professor)

  2. Department of Mathematics and Computer Science, Köthen University of Technology, Köthen, Germany

    C. Richter (Professor)

Authors
  1. H. Kleinmichel
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  2. C. Richter
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  3. K. Schönefeld
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Additional information

Communicated by O. L. Mangasarian

The authors thank the anonymous referees for their useful suggestions.

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Kleinmichel, H., Richter, C. & Schönefeld, K. On a class of hybrid methods for smooth constrained optimization. J Optim Theory Appl 73, 465–499 (1992). https://doi.org/10.1007/BF00940052

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