Reference : Differential Evolution Algorithms with Cellular Populations
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/16695
Differential Evolution Algorithms with Cellular Populations
English
Dorronsoro, Bernabé mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Bouvry, Pascal mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
2011
Lecture Notes in Computer Science
Springer
6239
320-330
Yes
International
0302-9743
1611-3349
[en] differntial evolution ; cellular populations
[en] Differential Evolution (DE) algorithms are efficient Evolutionary Algorithms (EAs) for the continuous optimization domain. There exist a large number of DE variants in the literature. In this paper, we analyze the effect of adding a cellular structure to the population of some of the most outstanding existing ones. The original algorithms will be compared versus their equivalent versions with cellular population both in terms of accuracy and convergence speed. As a result, we conclude that the cellular versions of the algorithms perform, in general, better than the equivalent state-of-the-art ones in the two considered issues.
University of Luxembourg: High Performance Computing - ULHPC
http://hdl.handle.net/10993/16695
10.1007/978-3-642-15871-1_33

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