Differential evolution for high scale dynamic optimization

Authors:
Miko$#322/aj Raciborski;Krzysztof Trojanowski;Piotr Kaczy$#324/ski
Affiliations:
Faculty of Mathematics and Natural Sciences, Cardinal Stefan Wyszy$#324/ski University, Warsaw, Poland;Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland;Faculty of Mathematics and Natural Sciences, Cardinal Stefan Wyszy$#324/ski University, Warsaw, Poland
Venue:
SIIS'11 Proceedings of the 2011 international conference on Security and Intelligent Information Systems
Year:
2011

Citing 11
Cited 0

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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.