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Studying The Rate Of Convergence Of The Steepest Descent Optimisation Algorithm With Relaxation

In: Computer Aided Methods In Optimal Design And Operations



    (Cardiff University, School of Mathematics, Senghennydd Road, Cardiff CF24 4AG, UK)


AbstractGradient-type algorithms can be linked to algorithms for constructing optimal experimental designs for linear regression models. The asymptotic rate of convergence of these algorithms can be expressed through the asymptotic behaviour of an experimental design construction procedure. One well known gradient-type algorithm is the method of Steepest Descent. Here a generalised version of the Steepest Descent algorithm, with a relaxation coefficient is considered and the rate of convergence of this algorithm is investigated.

Suggested Citation

  • R. J. Haycroft, 2006. "Studying The Rate Of Convergence Of The Steepest Descent Optimisation Algorithm With Relaxation," World Scientific Book Chapters,in: Computer Aided Methods In Optimal Design And Operations, chapter 6, pages 49-58 World Scientific Publishing Co. Pte. Ltd..
  • Handle: RePEc:wsi:wschap:9789812772954_0006

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    More about this item


    Optimization; Optimal Design; Global Optimization; Optimal Control;

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory


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