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Self-adjusting population sizes for non-elitist evolutionary algorithms: why success rates matter.

, and . GECCO, page 1151-1159. ACM, (2021)

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Analysing the Robustness of Evolutionary Algorithms to Noise: Refined Runtime Bounds and an Example Where Noise is Beneficial.. CoRR, (2018)Parallel Black-Box Complexity With Tail Bounds., and . IEEE Trans. Evol. Comput., 24 (6): 1010-1024 (2020)Hybridizing Evolutionary Algorithms with Variable-Depth Search to Overcome Local Optima.. Algorithmica, 59 (3): 343-368 (2011)Preface to the Special Issue on Theory of Genetic and Evolutionary Computation., and . Algorithmica, 81 (2): 589-592 (2019)On the Analysis of Trajectory-Based Search Algorithms: When is it Beneficial to Reject Improvements?, , , and . Algorithmica, 81 (2): 858-885 (2019)On the impact of the performance metric on efficient algorithm configuration., , and . Artif. Intell., (2022)Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem., , , and . CoRR, (2021)Analysis of speedups in parallel evolutionary algorithms and (1+λ) EAs for combinatorial optimization., and . Theor. Comput. Sci., (2014)The Cost of Randomness in Evolutionary Algorithms: Crossover can Save Random Bits., and . EvoCOP, volume 13987 of Lecture Notes in Computer Science, page 179-194. Springer, (2023)Do sophisticated evolutionary algorithms perform better than simple ones?, , , , , , and . GECCO, page 184-192. ACM, (2020)