Benchmarking CMA-EGS on the BBOB 2010 noisy function testbed

  • Authors:
  • Steffen Finck;Hans-Georg Beyer

  • Affiliations:
  • University of Applied Sciences Vorarlberg, Dornbirn, Austria;University of Applied Sciences Vorarlberg, Dornbirn, Austria

  • Venue:
  • Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
  • Year:
  • 2010

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Abstract

This paper describes the implementation and the results for CMA-EGS on the BBOB 2010 testbed. The CMA-EGS is a hybrid strategy which combines elements from gradient search and evolutionary algorithms. The paper describes the algorithm used and the experimental setup. The strategy is able to solve 17 of 30 functions in at least one dimensionality.