Accelerating the Convergence of Evolutionary Algorithms by Fitness Landscape Approximation

  title={Accelerating the Convergence of Evolutionary Algorithms by Fitness Landscape Approximation},
  author={Alain Ratle},
Abst rac t . A new algorithm is presented for accelerating the convergence of evolutionary optimization methods through a reduction in the number of fitness function calls. Such a reduction is obtained by 1) creating an approximate model of the fitness landscape using kriging interpolation, and 2) using this model instead of the original fitness function for evaluating some of the next generations. The main interest of the presented approach lies in problems for which the computational costs… CONTINUE READING


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Publications referenced by this paper.
Showing 1-9 of 9 references

Natural algorithms for choosing source locations in active control systems

  • K. H. Baek, S. J. Elliott
  • Journal of Sound and Vibration 186
  • 1995
1 Excerpt

Passive vibration control via unusual geometries: the application of genetic algorithm optimization to structural design

  • A. J. Keane
  • Journal of Sound and Vibration 185
  • 1995
1 Excerpt

An Overview of Evolutionary Algorithms for Parameter Optimization

  • T. Bick, Schwefel, H.-P.
  • Evolutionary Computation 1
  • 1993
1 Excerpt

Splines et krigeage: leur ~quivalence formeUe

  • G. Matheron
  • Technical Report N667, Centre de G~ostatistique…
  • 1980
1 Excerpt

The intrinsic random functions and their applications

  • G. Matheron
  • Adv. Appl. Prob. 5
  • 1973
1 Excerpt

Use of genetic algorithms for the vibroacoustic optimization of plate response

  • A. Ratle, A. Berry
  • Submitted to the Journal of the Acoustical…

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