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Energy Consumption of Evolutionary Algorithms in JavaScript

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Artificial Life and Evolutionary Computation (WIVACE 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1977))

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Abstract

Green computing is a methodology for saving energy when implementing algorithms. In environments where the runtime is an integral part of the application, it is essential to measure their energy efficiency so that researchers and practitioners have enough choice. In this paper, we will focus on JavaScript runtime environments for evolutionary algorithms; although not the most popular language for scientific computing, it is the most popular language for developers, and it has been used repeatedly to implement all kinds of evolutionary algorithms almost since its inception. In this paper, we will focus on the importance of measuring different versions of the same runtimes, as well as extending the EA operators that will be measured. We also like to remark on the importance of testing the operators in different architectures to have a more precise picture that tips the balance towards one runtime or another.

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Acknowledgements

This work is supported by the Ministerio español de Economía y Competitividad (Spanish Ministry of Competitivity and Economy) under project PID2020-115570GB-C22 (DemocratAI::UGR).

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Authors and Affiliations

  1. Department of Computer Engineering, Automatics and Robotics, University of Granada, Granada, Spain

    Juan J. Merelo-Guervós & Pedro A. Castillo

  2. Department of Graduate Studies, National Technological Institute of Mexico, Tijuana, Mexico

    Mario García-Valdez

Authors
  1. Juan J. Merelo-Guervós
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  2. Mario García-Valdez
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  3. Pedro A. Castillo
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Corresponding author

Correspondence to Juan J. Merelo-Guervós .

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Editors and Affiliations

  1. University of Modena and Reggio Emilia, Modena, Italy

    Marco Villani

  2. University of Parma, Parma, Italy

    Stefano Cagnoni

  3. University of Modena and Reggio Emilia, Modena, Italy

    Roberto Serra

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Merelo-Guervós, J.J., García-Valdez, M., Castillo, P.A. (2024). Energy Consumption of Evolutionary Algorithms in JavaScript. In: Villani, M., Cagnoni, S., Serra, R. (eds) Artificial Life and Evolutionary Computation. WIVACE 2023. Communications in Computer and Information Science, vol 1977. Springer, Cham. https://doi.org/10.1007/978-3-031-57430-6_1

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  • DOI: https://doi.org/10.1007/978-3-031-57430-6_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-57429-0

  • Online ISBN: 978-3-031-57430-6

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