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A branch and bound algorithm for bound constrained optimization problems without derivatives

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Abstract

In this paper, we give a new branch and bound algorithm for the global optimization problem with bound constraints. The algorithm is based on the use of inclusion functions. The bounds calculated for the global minimum value are proved to be correct, all rounding errors are rigorously estimated. Our scheme attempts to exclude most “uninteresting” parts of the search domain and concentrates on its “promising” subsets. This is done as fast as possible (by involving local descent methods), and uses little information as possible (no derivatives are required). Numerical results for many well-known problems as well as some comparisons with other methods are given.

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References

  1. Alefeld, G. and Herzberger, J. (1983),Introduction to Interval Computations, Academic Press, New York.

    Google Scholar 

  2. Boender, C., Kan, A. R., Timmer, G. and Stougie, L. (1982), A stochastic method for global optimization.Mathematical Programming,22: 125–140.

    Google Scholar 

  3. Brent, R. P. (1973),Algorithms for Minimization without Derivatives, Prentice-Hall Inc., Englewood Cliffs, New Jersey.

    Google Scholar 

  4. Charalambous, C. and Bandler, J. W. (1976), Non-linear minimax optimization as a sequence of leastpth optimization with finite values ofp.J. Comput. Syst. Sci. 7(4): 377–391.

    Google Scholar 

  5. Csendes, T. (1991), Test Results of Interval Methods for Global Optimization, 417–424, in E. Kaucher, S. M. Markov, G. Mayer,Computer Arithmetic, Scientific Computation and Mathematical Modelling, IMACS.

  6. Dixon, L. C. W. and Szegö, G. P. (eds.), (1975),Towards Global Optimization, North-Holland, Amsterdam.

    Google Scholar 

  7. Dixon, L. C. W. and Szegö, G. P. (eds.), (1978),Towards Global Optimization 2, North-Holland, Amsterdam.

    Google Scholar 

  8. Hansen, E. R. (1979), Global Optimization Using Interval Analysis —the One-Dimensional Case,J. Optim. Theor. and Appl. 29, 331–344.

    Google Scholar 

  9. Hansen, E. R. (1980), Global Optimization Using Interval Analysis —the Multidimensional Case,Numerische Mathematik 34, 247–270.

    Google Scholar 

  10. Hansen, E. R. (1992),Global Optimization Using Interval Analysis, Marcel Dekker Inc., New York.

    Google Scholar 

  11. Horst, R. and Tuy, H. (1990),Global Optimization, Springer-Verlag, Berlin.

    Google Scholar 

  12. Jansson, C. (1991), A Global Minimization Method: The One-Dimensional Case, Bericht 91.2 des Forschungsschwerpunktes Informations-und Kommunikationstechnik der TU Hamburg-Harburg.

  13. Jansson, C. (1992), A Global Optimization Method Using Interval Arithmetik. In L. Atanassova and J. Herzberger,Computer Arithmetic and Enclosure Methods, 259–267, North-Holland, Amsterdam.

    Google Scholar 

  14. Jansson, C. and Knüppel, O. (1992), A Global Minimization Method: The Multi-Dimensional Case, Bericht 92.1 des Forschungsschwerpunktes Informations-und Kommunikationstechnik der TU Hamburg-Harburg.

  15. Kearfott, B. Du, K. (1993) The Cluster Problem in Global Optimization,Computing Suppl. 9, 117–127.

    Google Scholar 

  16. Knüppel, O. (1993), BIAS —Basic Interval Arithmetic Subroutines, Bericht 93.3 des Forschungsschwerpunktes Informations-und Kommunikationstechnik der TU Hamburg-Harburg.

  17. Knüppel, O. (1993), PROFIL —Programmer's Runtime Optimized Fast Interval Library, Bericht 93.4 des Forschungsschwerpunktes Informations-und Kommunikationstechnik der TU Hamburg-Harburg.

  18. Knüppel, O. (1994), PROFIL/BIAS —A Fast Interval Library,Computing 53, 277–287.

    Google Scholar 

  19. Kulisch, U. and Miranker, W. L. (1981),Computer Arithmetic in Theory and Practice, Academic Press, New York.

    Google Scholar 

  20. Lohner, R. (1989), Enclosing all eigenvalues of symmetric matrices. InAccurate Numerical Algorithms, A Collection of Research Papers, volume 1 of Research Reports ESPRIT, Project 1072, DIAMOND, 87–103. Springer, Berlin.

    Google Scholar 

  21. Moore, R. E. (1966),Interval Analysis, Prentice-Hall, Englewood Cliffs, N.J.

    Google Scholar 

  22. Moore, R. E. (1976) On Computing the Range of Values of a Rational Function ofn Variables over a Bounded Region,Computing 16, 1–15.

    Google Scholar 

  23. Moore, R. E. (1979),Methods and Applications of Interval Analysis, SIAM, Philadelphia.

    Google Scholar 

  24. Moore, R., Hansen, E., and Leclerc, A. (1992), Rigorous Methods for Global Optimization. InRecent Advances in Global Optimization, Princeton series in computer science, 321–342. Princeton University Press, Princeton, New Jersey.

    Google Scholar 

  25. Murty, K. G. and Kabadi, S. N. (1987), Some NP-Complete Problems in Quadratic and Nonlinear Programming,Mathematical Programming 39, 117–130.

    Google Scholar 

  26. Neumaier, A. (1990),Interval Methods for Systems of Equations, Cambridge University Press.

  27. Pardalos, P. M. and Rosen, J. B. (1987),Constrained Global Optimization: Algorithms and Applications, Springer Lecture Notes Comp. Sci. 268, Berlin.

  28. Ratschek, H. (1985), Inclusion Functions and Global Optimization,Mathematical Programming 33, 300–317.

    Google Scholar 

  29. Ratschek, H. and Rokne, J. (1984),Computer Methods for the Range of Functions, Ellis Horwood Limited, Chichester.

    Google Scholar 

  30. Ratschek, H. and Rokne, J. (1988),New Computer Methods for Global Optimization, Ellis Horwood Limited, Chichester.

    Google Scholar 

  31. Ratz, D. (1992), An Inclusion Algorithm for Global Optimization in a Portable PASCAL-XSC Implementation, in L. Atanassova and J. Herzberger,Computer Arithmetic and Enclosure Methods, North-Holland, 329–339, Amsterdam.

    Google Scholar 

  32. Rump, S. M. (1983), Solving Algebraic Problems with High Accuracy, in U. W. Kulisch and W.L. Miranker (eds),A New Approach to Scientific Computation, Academic Press, New York.

    Google Scholar 

  33. Shen, Zuhe, Neumaier, A., and Eiermann, M.C. (1990), Solving Minimax Problems by Interval Methods,BIT 30, 742–751.

    Google Scholar 

  34. Skelboe, S. (1974), Computation of Rational Interval Functions,BIT 14, 87–95.

    Google Scholar 

  35. Törn, A. and Zilinskas, A. (1989),Global Optimization, Springer-Verlag, Berlin Heidelberg New York.

    Google Scholar 

  36. Walster, G., Hansen, E., and Sengupta, S., (1985), Test results for a global optimization algorithm.Numerical Optimization 1984, 272–287.

  37. Wilkinson, J. H. (1971), Modern error analysis,SIAM Rev. 13, 548–568.

    Google Scholar 

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Jansson, C., Knüppel, O. A branch and bound algorithm for bound constrained optimization problems without derivatives. J Glob Optim 7, 297–331 (1995). https://doi.org/10.1007/BF01279453

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