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Parallel algorithm portfolios with adaptive resource allocation strategy

Author

Listed:
  • Konstantinos E. Parsopoulos

    (University of Ioannina)

  • Vasileios A. Tatsis

    (University of Ioannina)

  • Ilias S. Kotsireas

    (Wilfrid Laurier University)

  • Panos M. Pardalos

    (University of Florida)

Abstract

Algorithm portfolios are multi-algorithmic schemes that combine a number of solvers into a joint framework for solving global optimization problems. A crucial part of such schemes is the resource allocation process that is responsible for assigning computational resources to the constituent algorithms. We propose a resource allocation process based on adaptive decision-making procedures. The proposed approach is incorporated in algorithm portfolios composed of three essential types of numerical optimization algorithms, namely gradient-based, direct search, and swarm intelligence algorithms. The designed algorithm portfolios are experimentally demonstrated on a challenging optimization problem for different dimensions and experimental settings. The accompanying statistical analysis offers interesting conclusions and insights on the performance of the algorithm portfolio compared to its constituent algorithms, as well as on the effect of its parameters.

Suggested Citation

  • Konstantinos E. Parsopoulos & Vasileios A. Tatsis & Ilias S. Kotsireas & Panos M. Pardalos, 2024. "Parallel algorithm portfolios with adaptive resource allocation strategy," Journal of Global Optimization, Springer, vol. 88(3), pages 685-705, March.
    • Handle: RePEc:spr:jglopt:v:88:y:2024:i:3:d:10.1007_s10898-022-01162-y
    DOI: 10.1007/s10898-022-01162-y
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    References listed on IDEAS

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    1. Wawrzyniak, Jakub & Drozdowski, Maciej & Sanlaville, Éric, 2020. "Selecting algorithms for large berth allocation problems," European Journal of Operational Research, Elsevier, vol. 283(3), pages 844-862.
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    Cited by:

    1. Ilias Kotsireas & Panos Pardalos & Julius Žilinskas, 2024. "Preface," Journal of Global Optimization, Springer, vol. 88(3), pages 531-532, March.

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