@inproceedings{9e2b78283d5f4057ad6e61aa924dfe55,
title = "Statistical multi-comparison of evolutionary algorithms",
abstract = "Performance benchmarking is an essential task in computational intelligence research. Evolutionary optimization algorithms are stochastic processes and to obtain significant results proper statistical tools must be used. This paper presents a step-by-step nonparametric comparison procedure able to assess the relative performance of several singleobjective evolutionary algorithms. This comparison procedure is based on a simple ranking scheme and is statistically relevant under a controlled risk of error. A useful feature of the procedure is the ability to visualize the dynamical behavior of the algorithms along with the confidence intervals of their performance. It also has the advantage of eliminating the use of arbitrary weighting coefficients when several comparisons criteria are involved.",
keywords = "Benchmarking, Evolutionary algorithms, Multiple comparisons",
author = "Mathieu Barrette and Tony Wong and \{De Kelper\}, Bruno and Pascal C{\^o}t{\'e}",
year = "2008",
language = "English",
isbn = "9789612640026",
series = "Bioinspired Optimization Methods and their Applications - Proceedings of the 3rd International Conference on Bioinspired Optimization Methods and their Applications, BIOMA 2008",
pages = "71--80",
booktitle = "Bioinspired Optimization Methods and their Applications - Proceedings of the 3rd International Conference on Bioinspired Optimization Methods and their Applications, BIOMA 2008",
note = "3rd International Conference on Bioinspired Optimization Methods and their Applications, BIOMA 2008 ; Conference date: 13-10-2008 Through 14-10-2008",
}