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Parallel Implementations Of Simulated Annealing

A local timing model for parallel optimization with Boltzmann Machines

  • Simulated Annealing
  • Conference paper
  • First Online:
Parallel Problem Solving from Nature (PPSN 1990)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 496))

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Abstract

It is well-known that synchronous fully parallel Boltzmann Machines do not asymptotically converge to an optimal solution in many optimization problems. Therefore the level of parallelism has to be reduced by an application specific partition of simultaneous active processing units. In this paper we present a local random timing model which automatically splits up the network in runtime controlled by a single global parameter. The speeding up of solving an optimization problem is discussed at the example of the TSP-problem.

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References

  1. Hinton, G.E., Sejnowski, T.J., Ackley, D.H.: "Boltzmann machines: constraint satisfaction network that learn", Carnegie-Mellon University (USA) Technical Report CMU-CS-84-119, (1984).

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Authors and Affiliations

  1. Lehrstuhl Bauelemente der Elektrotechnik, Universität Dortmund, Postfach 50 OS 00, D-4600, Dortmund 50, FRG

    Ingo Kreuzer & Karl Goser

Authors
  1. Ingo Kreuzer
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  2. Karl Goser
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Editor information

Hans-Paul Schwefel Reinhard Männer

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© 1991 Springer-Verlag Berlin Heidelberg

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Kreuzer, I., Goser, K. (1991). Parallel Implementations Of Simulated Annealing. In: Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature. PPSN 1990. Lecture Notes in Computer Science, vol 496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0029757

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  • DOI: https://doi.org/10.1007/BFb0029757

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54148-6

  • Online ISBN: 978-3-540-70652-6

  • eBook Packages: Springer Book Archive

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