Abstract
This article introduces a generic sensitivity analysis method to measure the influence and interdependencies of Evolutionary Algorithms parameters. The proposed work focuses on its application to a Parallel Asynchronous Cellular Genetic Algorithm (PA-CGA). Experimental results on two different instances of a scheduling problem have demonstrated that some metaheuristic parameters values have little influence on the solution quality. On the opposite, some local search parameter values have a strong impact on the obtained results for both instances. This study highlights the benefits of the method, which significantly reduces the parameter search space.
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Pinel, F., Danoy, G., Bouvry, P. (2012). Evolutionary Algorithm Parameter Tuning with Sensitivity Analysis. In: Bouvry, P., Kłopotek, M.A., Leprévost, F., Marciniak, M., Mykowiecka, A., Rybiński, H. (eds) Security and Intelligent Information Systems. SIIS 2011. Lecture Notes in Computer Science, vol 7053. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25261-7_16
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DOI: https://doi.org/10.1007/978-3-642-25261-7_16
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