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Distributed computing of a stochastic algorithm for combinatorial optimization problems

  • Combinatorial Optimization
  • Conference paper
  • First Online:
System Modelling and Optimization

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 113))

Abstract

Simulated annealing method, as a general stochastic algorithm, has proven to be particularly successful for combinatorial optimization problems. But it requires a long running time for some large scale problems. This paper introduces the synchronous and partially synchronous spatial process, instead of the Metropolis procedure, in the simulated annealing method, and shows the possibility of distributed computing. We use the module partition problem as an example to show the quality of the solutions obtained by our method and point out that a parallel computing is able to be executed to shorten the running time.

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References

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Authors and Affiliations

  1. Department of Computer Science, Tokyo Institute of Technology, Tokyo, Japan

    Zhao Yue & Takeshi Fukao

Authors
  1. Zhao Yue
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  2. Takeshi Fukao
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Editor information

Masao Iri Keiji Yajima

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© 1988 International Federation for Information Processing

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Yue, Z., Fukao, T. (1988). Distributed computing of a stochastic algorithm for combinatorial optimization problems. In: Iri, M., Yajima, K. (eds) System Modelling and Optimization. Lecture Notes in Control and Information Sciences, vol 113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0042800

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  • DOI: https://doi.org/10.1007/BFb0042800

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-19238-1

  • Online ISBN: 978-3-540-39164-7

  • eBook Packages: Springer Book Archive

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