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Implementing Pool-Based Evolutionary Algorithm in Amazon Cloud Computing Services

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Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization

Part of the book series: Studies in Computational Intelligence ((SCI,volume 601))

Abstract

In this article, we describe the implementation of a pool-based evolutionary algorithm on a cloud computing environment. We use the EvoSpace model for pool-based evolutionary algorithms (Pool-EA), which is designed to exploit cloud computing resources in order to generate better results than using a simple GA. The platform has been deployed in the cloud using Amazon services (Amazon EC2).

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References

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Acknowledgment

We would like to express our gratitude to the CONACYT and Tijuana Institute of Technology for the facilities and resources granted for the development of this research.

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Authors and Affiliations

  1. Tijuana Institute of Technology, Tijuana, BC, Mexico

    Rene Márquez Valenzuela & Mario García Valdez

Authors
  1. Rene Márquez Valenzuela
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  2. Mario García Valdez
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Corresponding author

Correspondence to Mario García Valdez .

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Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Patricia Melin

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

  3. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    Janusz Kacprzyk

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Valenzuela, R.M., Valdez, M.G. (2015). Implementing Pool-Based Evolutionary Algorithm in Amazon Cloud Computing Services. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization. Studies in Computational Intelligence, vol 601. Springer, Cham. https://doi.org/10.1007/978-3-319-17747-2_27

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  • DOI: https://doi.org/10.1007/978-3-319-17747-2_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17746-5

  • Online ISBN: 978-3-319-17747-2

  • eBook Packages: EngineeringEngineering (R0)

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