A study on the synchronization behaviour of differential evolution and a self-adaptive extension

• Autorzy: Santucci V. , Milani A. , Vella F.
• Języki publikacji: EN

Abstrakty

EN

Differential Evolution (DE) is a popular and efficient continuous optimization technique based on the principles of Darwinian evolution. Asynchronous Differential Evolution is a DE generalization that allows to regulate the synchronization mechanism of the algorithm by tuning two additional parameters. This paper, after providing a further experimental analysis of the impact of the DE synchronization scheme on the evolution, introduces three self-adaptive techniques to handle the synchronization parameters. Moreover the integration of these new regulatory synchronization techniques into state-of-the-art (self) adaptive DE schemes are also proposed. Experiments on widely accepted benchmark problems show that the new schemes are able to improve performances of the state-of-theart (self) adaptive DEs by introducing the new synchronization parameters in the online automated tuning process.

Słowa kluczowe

EN

synchronization; behaviour; differential evolution; DE; self-adaptive; extension; state of the art; adaptive DE

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2012
• Tom: Vol. 2, No. 4
• Strony: 279--301
• Opis fizyczny: Bibliogr. 42 poz., rys.

Twórcy

autor

Santucci V.

• Department of Mathematics and Computer Science, University of Perugia via Vanvitelli 1, 06123 Perugia, Italy

autor

Milani A.

• Department of Mathematics and Computer Science, University of Perugia via Vanvitelli 1, 06123 Perugia, Italy
• Department of Computer Science, Hong Kong Baptist University Kowloon Tong, Hong Kong, China

autor

Vella F.

• Department of Mathematics and Computer Science, University of Perugia via Vanvitelli 1, 06123 Perugia, Italy

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