Frequency and severity are a priori very influential parameters in the performance of Dynamic Optimization Problems because they establish when and how hard is the change of the target optimized function. We study in a systematic way their influence in the performance of Dynamic Optimization Problems and the possible mathematical correlations between them. Specifically, we have used a steady state Genetic Algorithm, which has been applied to three classic Dynamic Optimization Problems considering a wide range of frequency and severity values. The results show that the severity is the more important parameter influencing the accuracy of the algorithm. ©Springer-Verlag Berlin Heidelberg 2009.
CITATION STYLE
Alba, E., Luque, G., & Arias, D. (2009). Impact of frequency and severity on non-stationary optimization problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5484 LNCS, pp. 755–761). https://doi.org/10.1007/978-3-642-01129-0_85
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