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Some Limit Theorems on Simulated Annealing

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Stochastic Models, Statistical Methods, and Algorithms in Image Analysis

Part of the book series: Lecture Notes in Statistics ((LNS,volume 74))

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Abstract

Many combinatorial optimization problems can be described as finding the global minimum of a certain function U(•) over a finite state space S, say, {l, 2,…, N}. A commonly used approach is the gradient method. It takes “downhill” movements only. This guarantees a fast convergence. But it usually ends up with a local minimum, which might depend on the initial state.

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Authors and Affiliations

  1. Institute of Mathematics, Academia Sinica, Taipei, Taiwan

    T. S. Chiang, Y. Chow & J. Hsieh

Authors
  1. T. S. Chiang
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  2. Y. Chow
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  3. J. Hsieh
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Editor information

Editors and Affiliations

  1. Istituto per le Applicazioni del Calcolo, C.N.R., Viale del Policlinico 137, 00161, Rome, Italy

    Piero Barone  & Arnoldo Frigessi  & 

  2. Dipartimento di Matematica Pura ed Applicata, Università di L’Aquila, L’Aquila, Italy

    Mauro Piccioni

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© 1992 Springer-Verlag Berlin Heidelberg

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Chiang, T.S., Chow, Y., Hsieh, J. (1992). Some Limit Theorems on Simulated Annealing. In: Barone, P., Frigessi, A., Piccioni, M. (eds) Stochastic Models, Statistical Methods, and Algorithms in Image Analysis. Lecture Notes in Statistics, vol 74. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2920-9_8

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  • DOI: https://doi.org/10.1007/978-1-4612-2920-9_8

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-97810-9

  • Online ISBN: 978-1-4612-2920-9

  • eBook Packages: Springer Book Archive

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