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2020 – today
- 2022
[j4]Vladimir Stanovov
, Shakhnaz Akhmedova, Alexey Vakhnin, Evgenii Sopov, Eugene Semenkin, Michael Affenzeller:
Improving the Quantum Multi-Swarm Optimization with Adaptive Differential Evolution for Dynamic Environments. Algorithms 15(5): 154 (2022)- [j3]Aleksei Vakhnin, Evgenii Sopov:
A Novel Self-Adaptive Cooperative Coevolution Algorithm for Solving Continuous Large-Scale Global Optimization Problems. Algorithms 15(12): 451 (2022) - [c6]Shakhnaz Akhmedova, Vladimir Stanovov, Aleksei Vakhnin:
A hybrid self-adapting multi-swarm algorithm based on PSO and CMA-ES for continuous dynamic optimization. GECCO Companion 2022: 387-390 - 2021
- [j2]Alexey Vakhnin, Evgenii Sopov:
Investigation of Improved Cooperative Coevolution for Large-Scale Global Optimization Problems. Algorithms 14(5): 146 (2021) - 2020
- [j1]Alexey Vakhnin, Evgenii Sopov:
Investigation of the iCC Framework Performance for Solving Constrained LSGO Problems. Algorithms 13(5): 108 (2020) - [c5]Alexey Vakhnin, Evgenii Sopov:
Large-scale clustering using decomposition-based evolutionary algorithms. SSCI 2020: 345-352
2010 – 2019
- 2019
- [c4]Evgenii Sopov, Alexey Vakhnin:
Investigating the effects of population size and the number of subcomponents on the performance of SHADE algorithm with random adaptive grouping for LSGO problems. GECCO (Companion) 2019: 269-270 - [c3]Evgenii Sopov, Alexey Vakhnin:
A Decomposition-based Approach for Constrained Large-Scale Global Optimization. IJCCI 2019: 147-154 - 2018
- [c2]Alexey Vakhnin, Evgenii Sopov:
A Novel Method for Grouping Variables in Cooperative Coevolution for Large-scale Global Optimization Problems. ICINCO (1) 2018: 271-278 - [c1]Evgenii Sopov, Alexey Vakhnin:
An Investigation of Parameter Tuning in the Random Adaptive Grouping Algorithm for LSGO Problems. IJCCI 2018: 255-263
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