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AISB International Workshop on Evolutionary Computing

AISB EC 1997: Evolutionary Computing pp 275–286Cite as

An evolutionary, agent-assisted strategy for conceptual design space decomposition

  • Novel Techniques and Applications of Evolutionary algorithms
  • Conference paper
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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1305))

Abstract

Genetic algorithm based strategies for the rapid decomposition of complex, conceptual design spaces into discrete, bounded regions of high performance are described The objective is not to identify single peaks but to identify high performance regions. Sufficient regional cover (in terns of number of solutions) is required for the extraction of infomnation relating to design characteristics to support the designer in decision making processes for the definition of optimal design direction. Three strategies using single population and parallel GA implemertations are described and results are presented An adaptive filter is introduced to eliminate a need for apron knowledge of the design space. Rule-based agents complement the search process by exploring identified regions to define region bounds.

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References

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Authors and Affiliations

  1. Plymouth Engineering Design Centre, University of Plymouth, PL4 8AA, Drake Circus, Plymouth

    I. C. Parmee & M. A. Beck

Authors
  1. I. C. Parmee
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  2. M. A. Beck
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Editor information

David Corne Jonathan L. Shapiro

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© 1997 Springer-Verlag Berlin Heidelberg

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Parmee, I.C., Beck, M.A. (1997). An evolutionary, agent-assisted strategy for conceptual design space decomposition. In: Corne, D., Shapiro, J.L. (eds) Evolutionary Computing. AISB EC 1997. Lecture Notes in Computer Science, vol 1305. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0027181

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  • DOI: https://doi.org/10.1007/BFb0027181

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63476-8

  • Online ISBN: 978-3-540-69578-3

  • eBook Packages: Springer Book Archive

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