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Convergence Speed of an Integral Method for Computing the Essential Supremum

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Part of the Nonconvex Optimization and Its Applications book series (NOIA,volume 18)

Abstract

We give an equivalence between the tasks of computing the essential supremum of a summable function and of finding a certain zero of a one-dimensional convex function. Interpreting the integral method as Newton-type method we show that in the case of objective functions with an essential supremum that is not spread the algorithm can work very slowly. For this reason we propose a method of accelerating the algorithm which is in some respect similar to the method of Aitken/Steffensen.

Key words

  • essential supremum
  • convergence speed
  • integral global optimization
  • Newton algorithm

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References

  • Archetti, F. and Betrò, B. (1975), Recursive Stochastic Evaluation of the Level Set Measure in the Global Optimization Problems, Technical Report, University of Pisa, Pisa, Italy.

    Google Scholar 

  • Chichinadze, V.K. (1967), Random Search to Determine the Extremum of the Function of Several Variables, Engeneering Cybernetics 1, 115–123.

    Google Scholar 

  • Caselton, W.F, and Yassien, H. A. (1994), LSP4, public domain software, available via ftp://ftp.ruhr-uni-bochum.de/mirrors/simtel.coast.net/SimTel/msdos/statistic/lsp4.zip.

    Google Scholar 

  • Chew S.H. and Zheng Q. (1988), Integral Global Optimization, Springer, Berlin, Heidelberg.

    CrossRef  MATH  Google Scholar 

  • De Biase, L. and Frontini, F. (1978), A Stochastic Method for Global Optimization: Its Structure and Numerical Performance, in: Dixon, L.C.W. and Szegö, G.P. (eds.) (1978), Towards Global Optimization 2, North-Holland, Amsterdam, 85–102.

    Google Scholar 

  • Dieudonné, J. (1975), Grundzüge der modernen Analysis, Band III, Deutscher Verlag der Wissenschaften, Berlin.

    Google Scholar 

  • Hiriart-Urruty, J.-B. and Lemaréchal, C. (1993), Convex Analysis and Minimization Algorithms I, Springer, Berlin, Heidelberg.

    Google Scholar 

  • Kosmol, P. (1993), Methoden zur numerischen Behandlung nichtlinearer Gleichungen und Optimierungsaufgaben, Teubner, Stuttgart.

    Google Scholar 

  • Kostreva, M.M. and Zheng Q. (1994), Integral Global Optimization Method for Solution of Nonlinear Complementarity Problems, Journal of Global Optimization 5, 181–193.

    CrossRef  MathSciNet  MATH  Google Scholar 

  • Natanson, I.P. (1975), Theorie der Funktionen einer reellen Veränderlichen, Akademie-Verlag, Berlin.

    MATH  Google Scholar 

  • Phú, H.X. and Hoffmann, A. (1996), Essential Supremum and Supremum of Summable Functions, Numerical Functional Analysis and Optimization 17 (to appear).

    Google Scholar 

  • Stoer, J. (1994), Numerische Mathematik 1, Springer, Berlin, Heidelberg.

    MATH  Google Scholar 

  • Zheng Q. (1992), Integral Global Optimization of Robust Discontinuous Functions, Dissertation, Graduate School of Clemson University, Clemson.

    Google Scholar 

  • Zheng Q. and Zhuang D. (1995), Integral Global Minimization: Algorithms, Implementations and Numerical Tests, Journal of Global Optimization 7, 421–454.

    CrossRef  MathSciNet  MATH  Google Scholar 

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© 1997 Springer Science+Business Media Dordrecht

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Hichert, J., Hoffmann, A., Phú, H.X. (1997). Convergence Speed of an Integral Method for Computing the Essential Supremum. In: Bomze, I.M., Csendes, T., Horst, R., Pardalos, P.M. (eds) Developments in Global Optimization. Nonconvex Optimization and Its Applications, vol 18. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2600-8_10

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  • DOI: https://doi.org/10.1007/978-1-4757-2600-8_10

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-4768-0

  • Online ISBN: 978-1-4757-2600-8

  • eBook Packages: Springer Book Archive