Abstract
This paper studies properties of a differential evolution approach (DE) for dynamic optimization problems. An adaptive version of DE, namely the jDE algorithm has been applied to two well known benchmarks: Generalized Dynamic Benchmark Generator (GDBG) and Moving Peaks Benchmark (MPB). The experiments have been performed for different numbers of the search space dimensions starting from five until 30. The results show the influence of the problem complexity on the quality of the returned results both in case of varying and constant number of fitness function calls between subsequent changes.
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Raciborski, M., Trojanowski, K., Kaczyński, P. (2012). Differential Evolution for High Scale Dynamic Optimization. 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_14
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DOI: https://doi.org/10.1007/978-3-642-25261-7_14
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