|3/2012 - 6|
A Structure-Based Coarse-Fine Approach for Diversity Tuning in Cellular GAsMORALES-REYES, A. , ERDOGAN, A. T.
|View the paper record and citations in|
|Click to see author's profile in SCOPUS, IEEE Xplore, Web of Science|
|Download PDF (790 KB) | Citation | Downloads: 452 | Views: 2,570|
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)
Blue keywords are present in both the references section and the paper title.
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.
|References|||||Cited By «-- Click to see who has cited this paper|
| E. Alba and J. M. Troya, "A survey of parallel distributed genetic algorithms", Journal Complexity, Vol. 4, No. 4, pp. 31-52, 1999.
 E. Cantu-Paz, "A summary of research on parallel genetic algorithms," in IlliGAL report 95007, University of Illinois at Urbana-Champaign, 1995.
 C. L. S. Park and J. Kim, "Topology and migration policy of fine-grained parallel evolutionary algorithms for numerical optimization," in IEEE Congress on Evolutionary Computation, pp. 70-76, 2000.
[CrossRef] [SCOPUS Times Cited 9]
 T. Murata, K. Takada, "Performance evaluation of a distributed genetic algorithm with cellular structures on function optimization problems," in Proceedings of 8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems. Springer-Verlag, 2004, pp. 1128 - 1135.
[CrossRef] [SCOPUS Times Cited 2]
 S. Baluja, "Structure and performance of fine-grain parallelism in genetic search," technical report, Carnegie Mellon University, 1993.
 S. Gordon, K. Mathias, and D. Whitley, "Cellular genetic algorithms as function optimizers: Locality effects," in In Proceedings of the ACM Symposium on Applied Computing, pp. 237 - 241, 1994.
[CrossRef] [SCOPUS Times Cited 8]
 J. Sarma and K. D. Jong, "An analysis of the effects of neighborhood size and shape on local selection algorithms," in Parallel Problem Solving from Nature, pp. 236-244, Springer, 1996.
 E. Alba and B. Dorronsoro, "Cellular genetic algorithms," in Operations Research / Computer Science Interfaces, Springer, 2008.
[CrossRef] [SCOPUS Times Cited 67]
 E. Alba and B. Dorronsoro, "The exploration/exploitation tradeoff in dynamic cellular genetic algorithms," in IEEE Transactions on Evolutionary Computation, IEEE, 2005.
[CrossRef] [Web of Science Times Cited 238] [SCOPUS Times Cited 302]
 M. Kirley, X. Li, and D. G. Green, "Investigation of a cellular genetic algorithm that mimics landscape ecology," in Proceedings of SEAL98, Lecture Notes in Computer Science, pp. 90-97, Springer-Verlag Berlin Heidelberg, 1999.
[CrossRef] [SCOPUS Times Cited 18]
 E. Alba and J. Troya, "Improving flexibility and efficiency by adding parallelism to genetic algorithms," in Statistics and Computing, pp. 12(2):91-114, Kluwer Academic Publishers, 2002.
[CrossRef] [Web of Science Times Cited 58] [SCOPUS Times Cited 74]
 A. Morales-Reyes, E. Stefatos, A. Erdogan, and T. Arslan, "Towards fault-tolerant systems based on adaptive cellular genetic algorithms," in Proceedings of IEEE NASA/ESA Conference on Adaptive Hardware and Systems, pp. 398- 405, IEEE, 2008.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 14]
 D. A. Pierre, Optimization Theory with Applications. DOVER. 2nd. Edition, 1986.
 M. Kirley, "A cellular genetic algorithm with disturbances: Optimization using dynamic spatial interactions," Journal of Heuristics, Kluwer Academic Publishers, vol. 8, pp. 321-342, 2002.
[CrossRef] [Web of Science Times Cited 16] [SCOPUS Times Cited 34]
 A. Morales-Reyes, A. Erdogan, and T. Arslan, "Lattice reconfiguration vs. local selection criteria for diversity tuning in cellular gas," in Proceedings of the 2010 IEEE Congress on Evolutionary Computation, pp. 1 - 8, IEEE, 2010.
[CrossRef] [SCOPUS Times Cited 2]
 M. Giacobini, M. Tomassini, A. Tettamanzi, and E. Alba, "Selection intensity in cellular evolutionary algorithms for regular lattices," in IEEE Transactions on Evolutionary Computation, pp. 489-505, 2005.
[CrossRef] [Web of Science Times Cited 67] [SCOPUS Times Cited 79]
 D. Simoncini, P. Collard, S. Verel, and M. Clergue, "From cells to islands: An unified model of cellular parallel genetic algorithms," in Int. Conf. on Cellular Automata, pp. 248-257, Springer-Verlag, 2006.
[CrossRef] [SCOPUS Times Cited 5]
 D. Simoncini, P. Collard, S. Verel, and M. Clergue, "On the influence of selection operators on performances in cellular genetic algorithms," in Proceedings of IEEE Congress on Evolutionary Computation (CEC'07). IEEE, 2007, pp. 4706-4713.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 10]
 T. Back and R. Breukelaar, "Using genetic algorithms to evolve behaviour in cellular automata," in Lecture Notes in Computer Sciences 3699, pp. 1-10, Springer-Verlag, 2005.
[CrossRef] [SCOPUS Times Cited 17]
 M. Tomassini, "Spatially Structured Evolutionary Algorithms", Artificial Evolution in Space and Time. Springer. Series: Natural Computing Series, 2005.
 B. Dorronsoro and E. Alba, "A simple cellular genetic algorithm for continous optimization," in Proceedings of 2006 IEEE Congress on Evolutionary Computation, IEEE, 2006.
 H. Bersini, M. Dorigo, S. Langerman, G. Geront, and L. Gambardella, "Results of the first international contest on evolutionary optimization," in Proceedings of IEEE International Conference on Evolutionary Computation, pp. 611-615, IEEE, 1996.
[CrossRef] [Web of Science Times Cited 60]
 E. Stefatos and T. Arslan, "High-performance adaptive GPS attitude determination VLSI architecture," in IEEE Workshop on Signal Processing Systems, SIPS. IEEE, 2004, pp. 233-238.
 J. Xu, T. Arslan, Q. Wang, and D. Wan, "An EHW architecture for real-time GPS attitude determination based on parallel genetic algorithm," in Proceedings of Conference on Evolvable Hardware NASA/DoD, 2002, pp. 133-141.
 D. Ortiz-Boyer, C. Hervs-Martnez, and N. Garca-Pedrajas. (2008) Benchmark problems [Online] Available: Temporary on-line reference link removed - see the PDF document
Web of Science® Citations for all references: 452 TCR
SCOPUS® Citations for all references: 641 TCR
Web of Science® Average Citations per reference: 17 ACR
SCOPUS® Average Citations per reference: 25 ACR
TCR = Total Citations for References / ACR = Average Citations per Reference
We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more
Citations for references updated on 2021-11-21 16:54 in 102 seconds.
Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.