The theory of evolution strategies
The theory of evolution strategies
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Noisy Local Optimization with Evolution Strategies
Noisy Local Optimization with Evolution Strategies
A Comparison of Evolution Strategies with Other Direct Search Methods in the Presence of Noise
Computational Optimization and Applications
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
On the Asymptotic Behavior of Multirecombinant Evolution Strategies
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Learning probability distributions in continuous evolutionary algorithms– a comparative review
Natural Computing: an international journal
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Toward a theory of evolution strategies: On the benefits of sex---the (μ/μ, λ) theory
Evolutionary Computation
Toward a theory of evolution strategies: Self-adaptation
Evolutionary Computation
Evolutionary algorithms and gradient search: similarities anddifferences
IEEE Transactions on Evolutionary Computation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Weighted recombination evolution strategy on a class of PDQF's
Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic algorithms
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
Cumulative step length adaptation for evolution strategies using negative recombination weights
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Performance of the (µ/µ, λ)-σSA-ES on a class of PDQFs
IEEE Transactions on Evolutionary Computation
Log(λ) modifications for optimal parallelism
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Finding pre-images via evolution strategies
Applied Soft Computing
Noisy optimization: a theoretical strategy comparison of ES, EGS, SPSA & IF on the noisy sphere
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Mirrored sampling in evolution strategies with weighted recombination
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A median success rule for non-elitist evolution strategies: study of feasibility
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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Weighted recombination is a means for improving the local search performance of evolution strategies. It aims to make effective use of the information available, without significantly increasing computational costs per time step. In this paper, the potential speed-up resulting from using rank-based weighted multirecombination is investigated. Optimal weights are computed for the infinite-dimensional sphere model, and comparisons with the performance of strategies that do not make use of weighted recombination are presented. It is seen that unlike strategies that rely on unweighted recombination and truncation selection, weighted multirecombination evolution strategies are able to improve on the serial efficiency of the (1 + 1)-ES on the sphere. The implications of the use of weighted recombination for noisy optimization are studied, and parallels to the use of rescaled mutations are drawn. The significance of the findings is investigated in finite-dimensional search spaces.