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A parallel genetic clustering for inverse problems

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Applied Parallel Computing Large Scale Scientific and Industrial Problems (PARA 1998)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1541))

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Abstract

A parallel global optimization strategy for an ill posed inverse problem in computational mechanics is proposed. It contains a rough recognition of basins of attraction of local minima (clustering) with the use of genetic algorithms. Two levels of parallelism are involved. Basic asymptotic properties of the proposed genetic clustering will be proved. The computational example of the optimal pretractions design in a network structure (hanging roof) will be also shortly described.

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References

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Author information

Authors and Affiliations

  1. Institute of Computer Science, Jagiellonian University, Poland

    H Telega & R Schaefer

  2. Department of Civil Engineering, University of Udine, Italy

    E Cabib

Authors
  1. H Telega
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  2. R Schaefer
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  3. E Cabib
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Editor information

Bo Kågström Jack Dongarra Erik Elmroth Jerzy Waśniewski

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© 1998 Springer-Verlag Berlin Heidelberg

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Telega, H., Schaefer, R., Cabib, E. (1998). A parallel genetic clustering for inverse problems. In: Kågström, B., Dongarra, J., Elmroth, E., Waśniewski, J. (eds) Applied Parallel Computing Large Scale Scientific and Industrial Problems. PARA 1998. Lecture Notes in Computer Science, vol 1541. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095381

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  • DOI: https://doi.org/10.1007/BFb0095381

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65414-8

  • Online ISBN: 978-3-540-49261-0

  • eBook Packages: Springer Book Archive

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