Real-World problem for checking the sensitiveness of evolutionary algorithms to the choice of the random number generator

Authors:
Miguel Cárdenas-Montes;Miguel A. Vega-Rodríguez;Antonio Gómez-Iglesias
Affiliations:
Department of Fundamental Research, Centro de Investigaciones Energéticas Medioambientales y Tecnológicas, Madrid, Spain;ARCO Research Group, Dept. Technologies of Computers and Communications, University of Extremadura, Cáceres, Spain;National Laboratory of Fusion, Centro de Investigaciones Energéticas Medioambientales y Tecnológicas, Madrid, Spain
Venue:
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
Year:
2012

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Abstract

This article presents an analysis of the sensitiveness of evolutionary algorithms to the change of the random number generator when using a real-world problem --the fitting of a theoretical curve to an experimental data set-- as test. On the one hand, the evolutionary algorithms selected: particle swarm algorithm, differential evolution and genetic algorithm are widely used in optimization problems. And, on the other hand, the random number generator used: Mersenne Twister and GCC rand(), are the most frequently linked to evolutionary algorithms, as well as they are considered as high-quality. As a consequence of this work, an assessment is stated about the sensitiveness of the evolutionary algorithms studied to the choice of the random number generator.