期刊
SWARM AND EVOLUTIONARY COMPUTATION
卷 1, 期 1, 页码 3-18出版社
ELSEVIER
DOI: 10.1016/j.swevo.2011.02.002
关键词
Statistical analysis; Nonparametric statistics; Pairwise comparisons; Multiple comparisons; Evolutionary algorithms; Swarm intelligence algorithms
资金
- University of Granada
- [TIN2008-06681-C06-01]
The interest in non parametric statistical analysis has grown recently in the field of computational intelligence. In many experimental studies, the lack of the required properties for a proper application of parametric procedures - independence, normality, and homoscedasticity - yields to nonparametric ones the task of performing a rigorous comparison among algorithms. In this paper, we will discuss the basics and give a survey of a complete set of nonparametric procedures developed to perform both pairwise and multiple comparisons, for multi-problem analysis. The test problems of the CEC'2005 special session on real parameter optimization will help to illustrate the use of the tests throughout this tutorial, analyzing the results of a set of well-known evolutionary and swarm intelligence algorithms. This tutorial is concluded with a compilation of considerations and recommendations, which will guide practitioners when using these tests to contrast their experimental results. (C) 2011 Elsevier B.V. All rights reserved.
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