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International Conference on Parallel Problem Solving from Nature

PPSN 1996: Parallel Problem Solving from Nature — PPSN IV pp 1012–1021Cite as

Industrial plant pipe-route optimisation with genetic algorithms

  • Applications of Evolutionary Computation Evolutionary Computation in Mechanical, Chemical, Biological, and Optical Engineering
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1141))

Abstract

The pipe-route design problem for heavy industrial plant concerns minimising pipe material cost while satisfying constraints on required interconnections and obstacle avoidance. This process is invariably done by human experts, but modern stochastic iterative search techniques allow the opportunity to automate this process. This study explores the possibility of automated industrial pipe-route design on three test problems, using stochastic hillclimbing, simulated annealing, and genetic algorithms. The representation strategy is explained and discussed, and results are presented which show great promise for genetic algorithms in particular in this application area.

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References

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Author information

Authors and Affiliations

  1. School of Cognitive and Computing Sciences, University of Sussex at Brighton, BN1 9QH, Falmer, Brighton, UK

    Dae Gyu Kim

  2. Parallel, Emergent, and Distributed Architectures Laboratory (PEDAL), Department of Computer Science, University of Reading, RG6 2AY, Whiteknights, Reading, UK

    David Corne

  3. Department of Artificial Intelligence, University of Edinburgh, 80 South Bridge, EH1 1HN, Edin, UK

    Peter Ross

Authors
  1. Dae Gyu Kim
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  2. David Corne
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  3. Peter Ross
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Editor information

Hans-Michael Voigt Werner Ebeling Ingo Rechenberg Hans-Paul Schwefel

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© 1996 Springer-Verlag Berlin Heidelberg

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Kim, D.G., Corne, D., Ross, P. (1996). Industrial plant pipe-route optimisation with genetic algorithms. In: Voigt, HM., Ebeling, W., Rechenberg, I., Schwefel, HP. (eds) Parallel Problem Solving from Nature — PPSN IV. PPSN 1996. Lecture Notes in Computer Science, vol 1141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61723-X_1064

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  • DOI: https://doi.org/10.1007/3-540-61723-X_1064

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61723-5

  • Online ISBN: 978-3-540-70668-7

  • eBook Packages: Springer Book Archive

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