A service oriented evolutionary architecture: applications and results
Inhaltsverzeichnis
Referenz
Pablo García-Sánchez: A service oriented evolutionary architecture: applications and results. GECCO '13 Companion Proceedings of the 15th annual conference companion on Genetic and evolutionary computation, 1663-1666, 978-1-4503-1964-5.
DOI
http://dx.doi.org/10.1145/2464576.2482747
Abstract
This paper shows the stage of development of a Service Oriented Architecture for Evolutionary Algorithms and the first results obtained in two different areas. The abstract architecture is presented, with its assocciated implementation using a widely used technology. Results attained in experiments with parameter adaptation in distributed heterogeneous machines are presented and the usage of the architecture in Evolutionary Art is also applied.
Extended Abstract
Bibtex
@inproceedings{Garcia-Sanchez:2013:SOE:2464576.2482747,
author = {Garc\'{\i}a-S\'{a}nchez, Pablo},
title = {A Service Oriented Evolutionary Architecture: Applications and Results},
booktitle = {Proceedings of the 15th Annual Conference Companion on Genetic and Evolutionary Computation},
series = {GECCO '13 Companion},
year = {2013},
isbn = {978-1-4503-1964-5},
location = {Amsterdam, The Netherlands},
pages = {1663--1666},
numpages = {4},
url = {http://doi.acm.org/10.1145/2464576.2482747 http://geneura.ugr.es/~pgarcia/papers/2013/soahetero.pdf http://de.evo-art.org/index.php?title=A_service_oriented_evolutionary_architecture:_applications_and_results},
doi = {10.1145/2464576.2482747},
acmid = {2482747},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {distributed algorithms, evolutionary art, framework, island model, parameter setting, service oriented architecture},
}
Used References
1 E. Alba and G. Luque. Evaluation of parallel metaheuristics. In Parallel Problem Solving from Nature (PPSN), volume 4193 of Lecture Notes in Computer Science, pages 9--14, 2006.
2 Enrique Alba , Antonio J. Nebro , José M. Troya, Heterogeneous computing and parallel genetic algorithms, Journal of Parallel and Distributed Computing, v.62 n.9, p.1362-1385, September 2002 http://dx.doi.org/10.1006/jpdc.2002.1851
3 Rajkumar Buyya , Chee Shin Yeo , Srikumar Venugopal , James Broberg , Ivona Brandic, Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility, Future Generation Computer Systems, v.25 n.6, p.599-616, June, 2009 http://dx.doi.org/10.1016/j.future.2008.12.001
4 Peter J. Bentley , David W. Corne, Creative evolutionary systems, Morgan Kaufmann Publishers Inc., San Francisco, CA, 2001 http://dl.acm.org/citation.cfm?id=510349&CFID=558819604&CFTOKEN=68186175
5 A. Keane, The GRID: Computational and Data Resource Sharing in Engineering Optimisation and Design Search, Proceedings of the 2001 International Conference on Parallel Processing Workshops, p.207, September 03-07, 2001 http://dl.acm.org/citation.cfm?id=880224&CFID=558819604&CFTOKEN=68186175
6 I. Foster. Service-oriented science. Science, 308(5723):814, 2005.
7 C. Gagné and M. Parizeau. Genericity in evolutionary computation software tools: Principles and case-study. International Journal on Artificial Intelligence Tools, 15(2):173, 2006.
8 P. García-Sánchez, J. González, P.A. Castillo, M. G. Arenas, and J. J. Merelo-Guervós. Service oriented evolutionary algorithms. Soft Computing, pages 1--17, 2013. In press.
9 D. E. Goldberg, K. Deb, and J. Horn. Massive multimodality, deception, and genetic algorithms. In R. Männer and B. Manderick, editors, Parallel Problem Solving from Nature, 2, pages 37--48, Amsterdam, 1992. Elsevier Science Publishers, B. V.
10 Y. Gong and A. Fukunaga. Distributed island-model genetic algorithms using heterogeneous parameter settings. In Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2011, New Orleans, LA, USA, 5-8 June, 2011, pages 820--827. IEEE, 2011.
11 Yiyuan Gong , Morikazu Nakamura , Shiro Tamaki, Parallel genetic algorithms on line topology of heterogeneous computing resources, Proceedings of the 2005 conference on Genetic and evolutionary computation, June 25-29, 2005, Washington DC, USA http://doi.acm.org/10.1145/1068009.1068239
12 OSGi Alliance. OSGi service platform release 4.2, 2010. Available at: http://www.osgi.org/Release4/Download.
13 José Antonio Parejo , Antonio Ruiz-Cortés , Sebastián Lozano , Pablo Fernandez, Metaheuristic optimization frameworks: a survey and benchmarking, Soft Computing - A Fusion of Foundations, Methodologies and Applications, v.16 n.3, p.527-561, March 2012 http://dx.doi.org/10.1007/s00500-011-0754-8
14 Casey Reas , Ben Fry , John Maeda, Processing: A Programming Handbook for Visual Designers and Artists, The MIT Press, 2007
15 Carolina Salto , Enrique Alba, Designing heterogeneous distributed GAs by efficiently self-adapting the migration period, Applied Intelligence, v.36 n.4, p.800-808, June 2012 http://dx.doi.org/10.1007/s10489-011-0297-9
16 J. D. Schaffer and L. J. Eshelman. On Crossover as an Evolutionary Viable Strategy. In R. K. Belew and L. B. Booker, editors, Proceedings of the 4th International Conference on Genetic Algorithms, pages 61--68. Morgan Kaufmann, 1991.
Links
Full Text
http://geneura.ugr.es/~pgarcia/papers/2013/soahetero.pdf
