Benchmarking CMA-EGS on the BBOB 2010 noiseless 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 function 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 11 of 24 test functions for at least 5 of the 6 search space dimensionalities. For 4 test functions the target function value is not reached for at least one search space dimensionality.