Online vs. offline ANOVA use on evolutionary algorithms

Authors:
G. Romero;M. G. Arenas;P. A. Castillo;J. J. Merelo;A. M. Mora
Affiliations:
Dep. of Computer Architecture and Technology, University of Granada, Spain;Dep. of Computer Architecture and Technology, University of Granada, Spain;Dep. of Computer Architecture and Technology, University of Granada, Spain;Dep. of Computer Architecture and Technology, University of Granada, Spain;Dep. of Computer Architecture and Technology, University of Granada, Spain
Venue:
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Year:
2011

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Abstract

One of the main drawbacks of evolutionary algorithms is their great amount of parameters. Every step to lower this quantity is a step in the right direction. Automatic control of variation operators application rates during the run of an evolutionary algorithm is a desirable feature for two reasons: we are lowering the number of parameters of the algorithm and making it able to react changes in the conditions of the problem. In this paper, a dynamic breeder able to adapt the operators application rates over time following the evolutionary process is proposed. The decision to raise or to lower every rate is based on ANOVA to be sure of statistical significant.