2014 | OriginalPaper | Buchkapitel
Performance Testing of Multi-Chaotic Differential Evolution Concept on Shifted Benchmark Functions
verfasst von : Roman Senkerik, Michal Pluhacek, Donald Davendra, Ivan Zelinka, Zuzana Kominkova Oplatkova
Erschienen in: Hybrid Artificial Intelligence Systems
Verlag: Springer International Publishing
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This research deals with the hybridization of the two softcomputing fields, which are chaos theory and evolutionary computation. This paper aims on the investigations on the multi-chaos-driven evolutionary algorithm Differential Evolution (DE) concept. This paper is aimed at the embedding and alternating of set of two discrete dissipative chaotic systems in the form of chaos pseudo random number generators for the DE. In this paper the novel initial concept of DE/rand/1/bin strategy driven alternately by two chaotic maps (systems) is introduced. From the previous research, it follows that very promising results were obtained through the utilization of different chaotic maps, which have unique properties with connection to DE. The idea is then to connect these two different influences to the performance of DE into the one multi-chaotic concept. Repeated simulations were performed on the selected set of shifted benchmark functions in higher dimensions. Finally, the obtained results are compared with canonical DE.