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Evolutionary Algorithm Parameter Tuning with Sensitivity Analysis

  • Frédéric Pinel
  • Grégoire Danoy
  • Pascal Bouvry
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7053)

Abstract

This article introduces a generic sensitivity analysis method to measure the influence and interdependencies of Evolutionary Algorithms parameters. The proposed work focuses on its application to a Parallel Asynchronous Cellular Genetic Algorithm (PA-CGA). Experimental results on two different instances of a scheduling problem have demonstrated that some metaheuristic parameters values have little influence on the solution quality. On the opposite, some local search parameter values have a strong impact on the obtained results for both instances. This study highlights the benefits of the method, which significantly reduces the parameter search space.

Keywords

Evolutionary Algorithm Parameter Tuning Sensitivity Analysis 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Frédéric Pinel
    • 1
  • Grégoire Danoy
    • 1
  • Pascal Bouvry
    • 1
  1. 1.FSTC/CSC/ILIASUniversity of LuxembourgLuxembourg

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