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Multiscale Annealing and Robustness: Fast Heuristics for Large Scale Non-linear Optimization

In: Online Optimization of Large Scale Systems

Author

Listed:
  • Joachim M. Buhmann

    (Rheinische Friedrich-Wilhelm Universität, Institut für Informatik)

  • Jan Puzicha

    (University of California, Department of Computer Science)

Abstract

Multiscale Annealing is an extension of the idea of deterministic annealing which link the approximation quality of the algorithms to their effective spatial resolution. The optimization variables of a particular scale are linked together to reduce the spatial resolution, and, thereby, to simplify the computational complexity of the optimization task. Robustness and efficiency issues are discussed in this article on research questions of annealing techniques.

Suggested Citation

  • Joachim M. Buhmann & Jan Puzicha, 2001. "Multiscale Annealing and Robustness: Fast Heuristics for Large Scale Non-linear Optimization," Springer Books, in: Martin Grötschel & Sven O. Krumke & Jörg Rambau (ed.), Online Optimization of Large Scale Systems, pages 779-801, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-04331-8_37
    DOI: 10.1007/978-3-662-04331-8_37
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