Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Where Elitists Start Limping Evolution Strategies at Ridge Functions
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Step-Size Adaption Based on Non-Local Use of Selection Information
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Analysis of the (1, λ) - ES on the Parabolic Ridge
Evolutionary Computation
Analysis of the (μ/μ, λ) - ES on the Parabolic Ridge
Evolutionary Computation
Toward a theory of evolution strategies: Self-adaptation
Evolutionary Computation
On the performance of (1, λ)-evolution strategies for theridge function class
IEEE Transactions on Evolutionary Computation
Step length adaptation on ridge functions
Evolutionary Computation
Evolution strategies with cumulative step length adaptation on the noisy parabolic ridge
Natural Computing: an international journal
A gradient oriented recombination scheme for evolution strategies
Proceedings of the 2009 ACM symposium on Applied Computing
A novel approach to adaptive isolation in evolution strategies
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
On strategy parameter control by Meta-ES
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Cumulative step length adaptation for evolution strategies using negative recombination weights
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Population-based algorithm portfolios for numerical optimization
IEEE Transactions on Evolutionary Computation - Special issue on preference-based multiobjective evolutionary algorithms
Cumulative step length adaptation on ridge functions
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Information Sciences: an International Journal
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Organising evolution strategies hierarchically has been proposed as a means for adapting strategy parameters such as step lengths. Experimental research has shown that on ridge functions, hierarchically organised strategies can significantly outperform strategies that rely on mutative self-adaptation. This paper presents a first theoretical analysis of the behaviour of a hierarchically organised evolution strategy. Quantitative results are derived for the parabolic ridge that describe the dependence on the length of the isolation periods of the mutation strength and the progress rate. The issue of choosing an appropriate length of the isolation periods is discussed and comparisons with recent results for cumulative step length adaptation are drawn.