Comparison of Adaptive Approaches for Differential Evolution

  • Authors:
  • Karin Zielinski;Xinwei Wang;Rainer Laur

  • Affiliations:
  • Institute for Electromagnetic Theory and Microelectronics (ITEM), University of Bremen, Bremen, Germany 28334;Institute for Electromagnetic Theory and Microelectronics (ITEM), University of Bremen, Bremen, Germany 28334;Institute for Electromagnetic Theory and Microelectronics (ITEM), University of Bremen, Bremen, Germany 28334

  • Venue:
  • Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
  • Year:
  • 2008

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Abstract

The evaluation of optimization algorithms and especially the analysis of adaptive variants is often complicated because several features are modified concurrently. For Differential Evolution these features may be adaptation of parameters, adjustment of the strategy and addition of local search or other special operators. Thus, it is difficult to analyze which of these procedures is actually responsible for changes in the performance. Therefore, in this work several adaptive algorithms are studied in-depth by monitoring performance changes for individual components of these algorithms to examine their effectiveness. The results show among others that the performance can be significantly improved by employing strategy control.