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  1. 2026

  2. Quantum Optimized Crossover for the Travelling Salesman and Minimization of Makespan with Setup Times

    Eremeev, A. & Zakharova, Y., 13 Aug 2026, GECCO 2026 Companion - Proceedings of the 2026 Genetic and Evolutionary Computation Conference. Association for Computing Machinery, p. 1546-1549 4 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

  3. 2025

  4. Fitness Landscapes of Buffer Allocation Problem in Production Lines and Genetic Algorithms Performance

    Dolgui, A., Eremeev, A. & Sigaev, V., 11 Aug 2025, GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, p. 27-28 2 p. (GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

  5. On the Efficiency of Nonelitist Evolutionary Algorithms in the Case of Sparsity of the Level Sets Inconsistent with Respect to the Objective Function

    Eremeev, A. V., 10 Mar 2025, In: Proceedings of the Steklov Institute of Mathematics. 327, S1, p. S91-S111 21 p., 7.

    Research output: Contribution to journal › Article › peer-review

  6. On runtime of non-elitist evolutionary algorithms optimizing fitness functions with a plateau

    Еремеев, А. В., 2025, In: Yugoslav Journal of Operations Research. p. 1-27 27 p.

    Research output: Contribution to journal › Article › peer-review

  7. 2024

  8. Generalization of the Heavy-Tailed Mutation in the (1+(λ,λ)) Genetic Algorithm

    Eremeev, A. & Topchii, V., 14 Jul 2024, GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, p. 93-94 2 p. (GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

  9. Empirical Evaluation of Evolutionary Algorithms with Power-Law Ranking Selection

    Dang, D. C., Eremeev, A. V. & Qin, X., 2024, IFIP Advances in Information and Communication Technology. Springer, p. 217-232 16 p. (IFIP Advances in Information and Communication Technology; vol. 703 IFIPAICT).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › Research › peer-review

  10. Generalized Heavy-tailed Mutation for Evolutionary Algorithms

    Eremeev, A. V., Silaev, D. V. & Topchii, V. A., 2024, In: Siberian Electronic Mathematical Reports. 21, 2, p. 940-959 20 p.

    Research output: Contribution to journal › Article › peer-review

  11. On the efficiency of non-elitist evolutionary algorithms in the case of sparsity of the level sets inconsistent with respect to the objective function

    Eremeev, A. V., 2024, In: Trudy Instituta Matematiki i Mekhaniki UrO RAN. 30, 4, p. 84-105 22 p., 7.

    Research output: Contribution to journal › Article › peer-review

ID: 59828830