Already Moderate Population Sizes Provably Yield Strong Robustness to Noise-Reference-Cited by-同舟云学术

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Already Moderate Population Sizes Provably Yield Strong Robustness to Noise

Published:2024-07-14 Issue: Volume:24 Page:1524-1532
ISSN:
Container-title:Proceedings of the Genetic and Evolutionary Computation Conference
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Short-container-title:

Author:

Antipov Denis¹^ORCID,Doerr Benjamin²^ORCID,Ivanova Alexandra³⁴^ORCID

Affiliation:

1. Optimisation and Logistics, School of Computer and Mathematical Sciences, The University of Adelaide, Adelaide, South Australia, Australia

2. Laboratoire d'Informatique (LIX), École Polytechnique, Palaiseau, France

3. HSE University, Moscow, Russia

4. Skoltech, Moscow, Russia

Funder

FMJH Program Gaspard Monge for optimization and operations research and their interactions with data science

Australian Research Council

Publisher

ACM

Reference49 articles.

1. A Tight Runtime Analysis for the $${(\mu + \lambda )}$$ EA

2. Denis Antipov Benjamin Doerr and Alexandra Ivanova. 2024. Already Moderate Population Sizes Provably Yield Strong Robustness to Noise. (2024). arXiv:2404.02090

3. Anne Auger and Benjamin Doerr (Eds.). 2011. Theory of Randomized Search Heuristics. World Scientific Publishing.

4. Simplified Runtime Analysis of Estimation of Distribution Algorithms

5. Duc-Cuong Dang, Andre Opris, Bahare Salehi, and Dirk Sudholt. 2023. Analysing the robustness of NSGA-II under noise. In Genetic and Evolutionary Computation Conference, GECCO 2023. ACM, 642--651.

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