Hot off the Press: Runtime Analyses of Multi-Objective Evolutionary Algorithms in the Presence of Noise
Author:
Affiliation:
1. École Polytechnique, Palaiseau, France
2. Laboratoire d'Informatique (LIX), Palaiseau, France
Funder
FMJH Program Gaspard Monge
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3638530.3664070
Reference16 articles.
1. Dimo Brockhoff. 2011. Theoretical aspects of evolutionary multiobjective optimization. In Theory of Randomized Search Heuristics, Anne Auger and Benjamin Doerr (Eds.). World Scientific Publishing, 101--140.
2. Carlos Artemio Coello Coello, Gary B. Lamont, and David A. van Veldhuizen. 2007. Evolutionary Algorithms for Solving Multi-Objective Problems (2nd ed.). Springer.
3. Design and analysis of diversity-based parent selection schemes for speeding up evolutionary multi-objective optimisation
4. Analysing the Robustness of NSGA-II under Noise
5. A new analysis method for evolutionary optimization of dynamic and noisy objective functions
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