Comparison of cauchy EDA and BIPOP-CMA-ES algorithms on the BBOB noiseless testbed

Authors:
Petr Pošík
Affiliations:
Czech Technical University in Prague, Faculty of Electrical Engineering, Prague, Czech Rep
Venue:
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Year:
2010

Citing 4
Cited 0

BBOB-benchmarking a simple estimation of distribution algorithm with cauchy distribution

Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
BBOB-benchmarking the generalized generation gap model with parent centric crossover

Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
BBOB-benchmarking the Rosenbrock's local search algorithm

Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Benchmarking a BI-population CMA-ES on the BBOB-2009 function testbed

Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers

Quantified Score

Hi-index	0.00

Visualization

Abstract

Estimation-of-distribution algorithm using Cauchy sampling distribution is compared with the bi-population CMA evolutionary strategy which was one of the best contenders in the black-box optimization benchmarking workshop in 2009. The results clearly indicate that the CMA evolutionary strategy is in all respects a better optimization algorithm than the Cauchy estimation-of-distribution algorithm. This paper compares both algorithms in more detail and adds to the understanding of their key features and differences.