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A Structure-Based Coarse-Fine Approach for Diversity Tuning in Cellular GAsMORALES-REYES, A. , ERDOGAN, A. T.
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evolutionary computation, genetic algorithms, parallel algorithms, optimization, adaptive algorithm
genetic(16), cellular(14), algorithms(14), evolutionary(11), computation(7), parallel(6), optimization(6), alba(6), algorithm(5), systems(4)
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About this article
Date of Publication: 2012-08-31
Volume 12, Issue 3, Year 2012, On page(s): 39 - 46
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.03006
Web of Science Accession Number: 000308290500006
SCOPUS ID: 84865858905
This article empirically assesses a coarse-fine approach for diversity tuning in cellular Genetic Algorithms (cGAs). The coarse tuning is performed through the constant reconfiguration of the grid while the fine tuning is locally achieved through dynamic anisotropic selection which considers individuals' locations in the local neighborhood. Benchmark problems including continuous, real-world and combinatorial problems are evaluated. The experimental results show an improvement in cGAs performance when compared to having a fixed topology configuration or to independently applying dynamic lattice reconfiguration or dynamic anisotropic.
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 Improvement of the Gravitational Search Algorithm by means of Low-Discrepancy Sobol Quasi Random-Number Sequence Based Initialization, ALTINOZ, O. T., YILMAZ, A. E., WEBER, G.-W., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 14, 2014.
Digital Object Identifier: 10.4316/AECE.2014.03007 [CrossRef] [Full text]
 An Empirical Analysis on Dimensionality in Cellular Genetic Algorithms, Morales-Reyes, Alicia, Escalante, Hugo Jair, Letras, Martin, Cumplido, Rene, Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation, ISBN 9781450334723, 2015.
Digital Object Identifier: 10.1145/2739480.2754699 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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