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Boosting evolutionary algorithm configuration

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Abstract

Algorithm configuration has emerged as an essential technology for the improvement of high-performance solvers. We present new algorithmic ideas to improve state-of-the-art solver configurators automatically by tuning. Particularly, we introduce 1. a forward-simulation method to improve parallel performance, 2. an improvement to the configuration process itself, and 3. a new technique for instance-specific solver configuration. Extensive experimental results show that the new solver configurator compares very favorably with the state-of-the-art in automatic configuration for combinatorial solvers.

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Acknowledgments

This work was partially supported by the MINECO-FEDER project TASSAT3 (TIN2016-76573-C2-2-P) and the MICINN project PROOFS (PID2019-109137GBC21).

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Authors and Affiliations

  1. Logic & Optimization Group (LOG), University of Lleida, Lleida, Spain

    Carlos Ansótegui & Josep Pon

  2. General Electric, Boston, MA, USA

    Meinolf Sellmann

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  1. Carlos Ansótegui
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  2. Josep Pon
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  3. Meinolf Sellmann
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Correspondence to Josep Pon.

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Ansótegui, C., Pon, J. & Sellmann, M. Boosting evolutionary algorithm configuration. Ann Math Artif Intell 90, 715–734 (2022). https://doi.org/10.1007/s10472-020-09726-y

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  • DOI: https://doi.org/10.1007/s10472-020-09726-y

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