Fast mutation in crossover-based algorithms D Antipov, M Buzdalov, B Doerr
Proceedings of the 2020 Genetic and Evolutionary Computation Conference …, 2020
50 2020 Runtime analysis of a heavy-tailed genetic algorithm on jump functions D Antipov, B Doerr
International Conference on Parallel Problem Solving from Nature, 545-559, 2020
36 2020 Lazy parameter tuning and control: choosing all parameters randomly from a power-law distribution D Antipov, M Buzdalov, B Doerr
Proceedings of the Genetic and Evolutionary Computation Conference, 1115-1123, 2021
31 2021 The (1 + (λ,λ )) GA is even faster on multimodal problems D Antipov, B Doerr, V Karavaev
Proceedings of the 2020 Genetic and Evolutionary Computation Conference …, 2020
29 2020 A tight runtime analysis for the (1+(λ, λ)) GA on LeadingOnes D Antipov, B Doerr, V Karavaev
Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic …, 2019
26 2019 The efficiency threshold for the offspring population size of the (µ, λ ) EA D Antipov, B Doerr, Q Yang
Proceedings of the Genetic and Evolutionary Computation Conference, 1461-1469, 2019
24 2019 A tight runtime analysis for the (μ+ λ) EA D Antipov, B Doerr, J Fang, T Hetet
Proceedings of the Genetic and Evolutionary Computation Conference, 1459-1466, 2018
24 2018 A Rigorous Runtime Analysis of the GA on Jump Functions D Antipov, B Doerr, V Karavaev
Algorithmica 84 (6), 1573-1602, 2022
22 2022 Runtime analysis for the (µ+ λ) EA optimizing OneMax D Antipov, B Doerr, J Fang, T Hetet
Genetic and Evolutionary Computation Conference, GECCO, 1459-1466, 2018
22 2018 First steps towards a runtime analysis when starting with a good solution D Antipov, M Buzdalov, B Doerr
International Conference on Parallel Problem Solving from Nature, 560-573, 2020
20 2020 Precise runtime analysis for plateaus D Antipov, B Doerr
International Conference on Parallel Problem Solving from Nature, 117-128, 2018
16 2018 Coevolutionary Pareto diversity optimization A Neumann, D Antipov, F Neumann
Proceedings of the Genetic and Evolutionary Computation Conference, 832-839, 2022
14 2022 Precise runtime analysis for plateau functions D Antipov, B Doerr
ACM Transactions on Evolutionary Learning and Optimization 1 (4), 1-28, 2021
10 2021 Using 3-objective evolutionary algorithms for the dynamic chance constrained knapsack problem IH Pathiranage, F Neumann, D Antipov, A Neumann
arXiv preprint arXiv:2404.06014, 2024
8 2024 Effective 2-and 3-objective MOEA/D approaches for the chance constrained knapsack problem IH Pathiranage, F Neumann, D Antipov, A Neumann
Genetic and Evolutionary Computation Conference, GECCO, 2024
7 2024 Rigorous Runtime Analysis of Diversity Optimization with GSEMO on OneMinMax D Antipov, A Neumann, F Neumann
Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic …, 2023
5 2023 The effect of non-symmetric fitness: The analysis of crossover-based algorithms on RealJump functions D Antipov, S Naumov
Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic …, 2021
5 2021 A tight runtime analysis for the (𝜇+ 𝜆) EA D Antipov, B Doerr
Algorithmica 83 (4), 1054-1095, 2021
5 2021 Theoretical and empirical study of the (1+(λ, λ)) EA on the LeadingOnes problem V Karavaev, D Antipov, B Doerr
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019
5 2019 Efficient computation of fitness function for evolutionary clustering S Muravyov, D Antipov, A Buzdalova, A Filchenkov
Mendel 25 (1), 87-94, 2019
3 2019