Boosting evolutionary algorithm configuration

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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Correspondence to Josep Pon.

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Ansótegui, C., Pon, J. & Sellmann, M. Boosting evolutionary algorithm configuration. Ann Math Artif Intell (2021). https://doi.org/10.1007/s10472-020-09726-y

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Keywords

  • Genetic algorithms
  • Algorithm configuration
  • Algorithm portfolios

Mathematics Subject Classification (2010)

  • 68