Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Learning probability distributions in continuous evolutionary algorithms– a comparative review
Natural Computing: an international journal
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Hierarchically organised evolution strategies on the parabolic ridge
Proceedings of the 8th annual conference on Genetic and evolutionary computation
An analysis of mutative σ-self-adaptation on linear fitness functions
Evolutionary Computation
Step length adaptation on ridge functions
Evolutionary Computation
Mutative self-adaptation on the sharp and parabolic ridge
FOGA'07 Proceedings of the 9th international conference on Foundations of genetic algorithms
Searching for balance: understanding self-adaptation on ridge functions
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Clustering-based hierarchical genetic algorithm for complex fitness landscapes
International Journal of Intelligent Systems Technologies and Applications
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Hierarchically organised evolution strategies have been seen to be able to successfully adapt step lengths where mutative self-adaptation fails. However, the computational costs of such strategies are high due to the need to evolve several subpopulations in isolation, and their performance depends crucially on the length of the isolation periods. This paper proposes a novel approach to adapting the length of the isolation periods that is found to robustly generate good settings across a range of test functions.