A study on the use of non-parametric tests for analyzing the evolutionary algorithms' behaviour: a case study on the CEC'2005 Special Session on Real Parameter Optimization

  • Authors:

  • Salvador García;Daniel Molina;Manuel Lozano;Francisco Herrera

  • Affiliations:

  • Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain 18071;Department of Computer Engineering, University of Cádiz, Cádiz, Spain;Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain 18071;Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain 18071

  • Venue:
  • Journal of Heuristics
  • Year:
  • 2009

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Abstract

In recent years, there has been a growing interest for the experimental analysis in the field of evolutionary algorithms. It is noticeable due to the existence of numerous papers which analyze and propose different types of problems, such as the basis for experimental comparisons of algorithms, proposals of different methodologies in comparison or proposals of use of different statistical techniques in algorithms' comparison.In this paper, we focus our study on the use of statistical techniques in the analysis of evolutionary algorithms' behaviour over optimization problems. A study about the required conditions for statistical analysis of the results is presented by using some models of evolutionary algorithms for real-coding optimization. This study is conducted in two ways: single-problem analysis and multiple-problem analysis. The results obtained state that a parametric statistical analysis could not be appropriate specially when we deal with multiple-problem results. In multiple-problem analysis, we propose the use of non-parametric statistical tests given that they are less restrictive than parametric ones and they can be used over small size samples of results. As a case study, we analyze the published results for the algorithms presented in the CEC'2005 Special Session on Real Parameter Optimization by using non-parametric test procedures.