Genetic Algorithms and their Application to the Identification of Hydraulic Properties of Rocks

  • N. S. Mera
  • D. B. Ingham
  • L. Elliott
Conference paper
Part of the NATO Science Series book series (NAII, volume 134)


Many of the problems encountered in engineering may be reformulated as optimisation problems but often the corresponding objective function may be highly nonlinear or non-monotonie, may have a very complex form or its analytical expression may be unknown. Traditional, gradient based, optimisation algorithms are likely to fail for objective functions that exhibit multiple local optima and for such a gradient based algorithms in practice it is often difficult to provide an initial guess which is within the radius of convergence towards the global optimum. Also, in order to achieve convergence various restrictions are imposed and the applicability of such gradient algorithms is limited since these requirements are rarely met in practice. Moreover, gradient computations may constitute a problem in itself if noise is present in the measurements. Therefore, for complex practical problems, often it is required to use a more robust and adaptive approach.


Genetic Algorithm Hydraulic Conductivity Boundary Element Method Rock Specimen Sensitivity Coefficient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media Dordrecht 2004

Authors and Affiliations

  • N. S. Mera
    • 1
  • D. B. Ingham
    • 2
  • L. Elliott
    • 2
  1. 1.Centre for Computational Fluid Dynamics Energy and Resources Research InstituteUniversity of LeedsLeedsUK
  2. 2.Department of Applied MathematicsUniversity of LeedsLeedsUK

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