A Methodology to Develop Service Oriented Evolutionary Algorithms

  • P. García-Sánchez
  • A. M. Mora
  • P. A. Castillo
  • J. González
  • J. J. Merelo
Part of the Studies in Computational Intelligence book series (SCI, volume 570)

Abstract

This paper proposes a methodology to design and implement Evolutionary Algorithms using the Service Oriented Architecture paradigm. This paradigm allows to deal with some of the shortcomings in the Evolutionary Algorithms area, facilitating the development, integration, standardization of services that conform a evolutionary algorithm, and, besides, the dynamic alteration of those elements in runtime. A four-step methodology to design services for Evolutionary Algorithms is presented: identification, specification, implementation and deployment. Also, as an example of application of this methodology, an adaptive algorithm is developed.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Eiben, A., Smith, J.: What is an Evolutionary Algorithm? In: Introduction to Evolutionary Computing. Springer (2003)Google Scholar
  2. 2.
    Meri, K., Arenas, M.G., Mora, A.M., Merelo, J., Castillo, P.A., García-Sánchez, P., Laredo, J.L.J.: Cloud-based evolutionary algorithms: An algorithmic study. Natural Computing, 1–13 (2013)Google Scholar
  3. 3.
    García-Sánchez, P., González, J., Castillo, P.A., Arenas, M.G., Merelo-Guervós, J.J.: Service oriented evolutionary algorithms. Soft Comput. 17(6), 1059–1075 (2013)CrossRefGoogle Scholar
  4. 4.
    Arsanjani, A., Ghosh, S., Allam, A., Abdollah, T., Ganapathy, S., Holley, K.: SOMA: A method for developing service-oriented solutions. IBM Systems Journal 47(3), 377–396 (2008)CrossRefGoogle Scholar
  5. 5.
    Foster, I.: Service-oriented science. Science 308(5723), 814 (2005)CrossRefGoogle Scholar
  6. 6.
    Imade, H., Morishita, R., Ono, I., Ono, N., Okamoto, M.: A grid-oriented genetic algorithm framework for bioinformatics. New Generation Computing 22(2), 177–186 (2004)CrossRefMATHGoogle Scholar
  7. 7.
    Gagné, C., Parizeau, M.: Genericity in evolutionary computation software tools: Principles and case-study. International Journal on Artificial Intelligence Tools 15(2), 173 (2006)CrossRefGoogle Scholar
  8. 8.
    Valipour, M., Amirzafari, B., Maleki, K., Daneshpour, N.: A brief survey of software architecture concepts and service oriented architecture. In: 2nd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2009, pp. 34–38 (2009)Google Scholar
  9. 9.
    Goldberg, D.E., Deb, K., Horn, J.: Massive multimodality, deception, and genetic algorithms. In: Männer, R., Manderick, B. (eds.) Parallel Problem Solving from Nature, vol. 2, pp. 37–48. Elsevier Science Publishers, B. V., Amsterdam (1992)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • P. García-Sánchez
    • 1
  • A. M. Mora
    • 1
  • P. A. Castillo
    • 1
  • J. González
    • 1
  • J. J. Merelo
    • 1
  1. 1.Dept. of Computer Architecture and Technology and CITIC-UGRUniversity of GranadaGranadaSpain

Personalised recommendations