Eremeev A. and Topchii V. Asymptotical analysis of the (1+(lambda,lambda)) GA escape time from local optima on Jump functions. arXiv:2607.14278v2 [cs.NE]
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Eremeev A., Silaev D. and Topchii V. Improved upper bound of the (1 + (lambda, lambda)) GA escape time from local optima on Jump functions. In Genetic and Evolutionary Computation Conference (GECCO ’26 Companion), July 13–17, 2026, San Jose, Costa Rica. ACM, New York, NY, USA, pp. 709-712. DOI: 10.1145/3795101.3805384.
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Eremeev A., Zakharova Yu. Quantum optimized crossover for the travelling salesman and minimization of makespan with setup times. In Genetic and Evolutionary Computation Conference (GECCO ’26 Companion), July 13–17, 2026, San Jose, Costa Rica. ACM, New York, NY, USA, pp. 1546-1549. DOI: 10.1145/3795101.3814656.
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A.V. Eremeev, D.V. Silaev, V.A. Topchii. Generalized heavy-tailed mutation for evolutionary algorithms. arXiv:2604.00502 [cs.NE]
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A.V. Eremeev. On Runtime of Non-Elitist Evolutionary Algorithms Optimizing Fitness Functions with a Plateau. Yugoslav Journal of Operations Research. 2025. Online First. DOI: 10.2298/yjor250715042e.
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Eremeev A., Topchii V. Application of Limit Theorems to Runtime Analysis of the (1+(lambda,lambda)) Genetic Algorithm. In Genetic and Evolutionary Computation Conference (GECCO ’25 Companion), July 14–18, 2025, Malaga, Spain. ACM, New York, NY, USA, pp. 975 - 978. DOI: 10.1145/3712255.3726625.
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Eremeev A., Topchii V. Generalization of the heavy-tailed mutation in the (1+(lambda,lambda)) genetic algorithm. Proc. of GECCO 2024 Companion, pp. 93-94. DOI: 10.1145/3638530.3664095. A self-archived version is available here.
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D.-C. Dang, A.V. Eremeev, P.K. Lehre, X. Qin. Fast non-elitist evolutionary algorithms with power-law ranking selection. Proc. of GECCO 2022, pp. 1372–1380. Full text.
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D.-C. Dang, A.V. Eremeev, P.K. Lehre. Non-elitist evolutionary algorithms excel in fitness landscapes with sparse deceptive regions and dense valleys. Proc. of GECCO 2021, pp. 1133-1141. Full text. Note the corrigendum to this paper.
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D.-C. Dang, A.V. Eremeev, P.K. Lehre. Escaping Local Optima with Non-Elitist Evolutionary Algorithms. Proc. of AAAI 2021, pp. 12275-12283.
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A.V. Eremeev Runtime Analysis of Non-Elitist Evolutionary Algorithms with Fitness-Proportionate Selection on Royal Road Functions. 2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020. International conference. Novosibirsk, Russia, IEEE, 2020. pp. 228-232. Self-archived version is available here.
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Eremeev A.V. Runtime Analysis of Non-Elitist Evolutionary Algorithms with Fitness-Proportionate Selection on Royal Road Functions. 2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020. International conference. Novosibirsk, Russia, IEEE, 2020. pp. 228-232. Self-archived version is available here.
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Eremeev A.V. On non-elitist evolutionary algorithms optimizing fitness functions with a plateau. Proc. of International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2020, Novosibirsk, Russia, July 6-10, 2020 / Ed. by Kononov A., Khachay M., Kalyagin V., Pardalos P. Lecture Notes in Computer Science, vol. 12095, Springer, Cham. 2020. pp.329-342. Self-archived version is available here.
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D.-C. Dang, A.V. Eremeev, P.K. Lehre. Runtime Analysis of Fitness-Proportionate Selection on Linear Functions. arXiv:1908.08686v1 [cs.NE]
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A. Eremeev and A. Spirov. Estimates from evolutionary algorithms theory applied to gene design. In: 11th International Multiconference Bioinformatics of Genome Regulation and Structure\Systems Biology (BGRS\SB), IEEE, 2018, pp. 33-38. DOI: 10.1109/CSGB.2018.8544837. Preliminary version available here.
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D. Corus, D.-C. Dang, A.V. Eremeev, P.K. Lehre. Level-based analysis of genetic algorithms and other search processes, IEEE Transactions on Evolutionary Computation, 2018, Vol. 22, Issue 5, pp. 707-719. DOI: 10.1109/TEVC.2017.2753538. Preliminary version: arXiv:1407.7663v2 [cs.NE]
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A.V. Eremeev. On proportions of fit individuals in population of mutation-based evolutionary algorithm with tournament selection. Evolutionary Computation, Vol. 26, Issue 2, 2018, pp.269-297. DOI:10.1162/EVCO_a_00210. Preliminary version is available here.
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A.V. Eremeev. Hitting times of local and global optima in genetic algorithms with very high selection pressure. Yugoslav Journal of Operations Research. 2017. Vol. 27, Issue 3, pp. 323-339. DOI: 10.2298/YJOR160318016E.
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A.V. Eremeev. and J.V. Kovalenko Experimental Evaluation of Two Approaches to Optimal Recombination for Permutation Problems. In: F. Chicano, B. Hu, P. Garcia-Sanchez (Eds.) Proceedings of Evolutionary Computation in Combinatorial Optimization (EvoCOP 2016) LNCS Vol. 9595, 2016. pp. 138-153. The original publication is available at http://dx.doi.org/10.1007/978-3-319-30698-8_10. © Springer-Verlag.
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D. Corus, D.-C. Dang, A.V. Eremeev, P.K. Lehre. Level-based analysis of genetic algorithms and other search processes Proc. of Parallel Problem Solving from Nature (PPSN XIII). Ljubljana, Slovenia, 2014. Proceedings. Springer, LNCS 8672. 2014. P. 912-921.
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A.V. Eremeev, J.V. Kovalenko. Optimal recombination in genetic algorithms for combinatorial optimization problems: Part I. Yugoslav Journal of Operations Research. Vol. 24. N 1. 2014. P. 1-20.
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A.V. Eremeev, J.V. Kovalenko. Optimal recombination in genetic algorithms for combinatorial optimization problems: Part II. Yugoslav Journal of Operations Research. Vol. 24. N 2. 2014. P. 165-186.
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A.V. Eremeev. Non-elitist genetic algorithm as a local search method. Preprint (arXiv:1307.3463v2 [cs.NE]). 2013. 9 p.
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A.V. Eremeev. On complexity of optimal recombination for the Travelling Salesman Problem. In: Peter Merz Jin-Kao Hao (Eds.) Proceedings of Evolutionary Computation in Combinatorial Optimization (EvoCOP 2011) LNCS Vol. 6622, 2011. pp. 215-225. The original publication is available at www.springerlink.com. © Springer-Verlag.
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B. Doerr, A. Eremeev, F. Neumann, M. Theile, C. Thyssen. Evolutionary algorithms and dynamic programming. Theoretical Computer Science. Vol. 412. Issue 43. 2011. P.6020-6035.
The original publication is available here.
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A. V. Eremeev. On complexity of optimal recombination for binary representations of solutions. Evolutionary Computation, 16 (1), 2008, pp. 127-147. © MIT Press Abstract >>>

P. A. Borisovsky A. V. Eremeev. Comparing Evolutionary Algorithms to the (1+1)-EA. Theoretical Computer Science. 403 (1), 2008, pp. 33-41. DOI: 10.1016/j.tcs.2008.03.008. © Elsevier Science. A draft version is available here.
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P. A. Borisovskii, A. V. Eremeev. Comparison of Certain Evolutionary Algorithms. Automation and Remote Control, Vol. 65, N 3, 2004, pp. 357-362. DOI: 10.1023/B:AURC.0000019365.10288.58
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P.A.Borisovsky, A.V.Eremeev. A Study on Performance of the (1+1)-Evolutionary Algorithm. In K. De Jong, R. Poli, and J. Rowe, eds. Foundations of Genetic Algorithms 7. San Francisco. Morgan Kaufmann. 2003. pp. 271-287. © 2003 by Morgan Kaufmann, An Imprint of Elsevier Science. All rights reserved.
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A.V.Eremeev, C.R.Reeves. Evolutionary algorithms in discrete optimisation. Book of abstracts of Discrete Analysis and Operations Research Conference (DAOR-2002). Novosibirsk, Russia. pp.40-45. Abstract >>>

P.A.Borisovsky, A.V. Eremeev. On Performance Estimates for Two Evolutionary Algorithms. In E.J.W.Boers et al. (Eds.) Applications of evolutionary computing: Proceedings of EvoWorkshops 2001. LNCS Vol. 2037, 2001. pp. 161-171. © Springer-Verlag.
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A.V. Eremeev. Modelling and Analysis of Genetic Algorithm with Tournament Selection. (A shorter version of this paper is published in Proceedings of Artificial Evolution'99, LNCS Vol. 1829, 2000. pp. 84-95. © Springer-Verlag.)
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A. Eremeev and A. Spirov. Modeling SELEX for regulatory regions using Royal Road and Royal Staircase fitness functions. Biosystems. vol. 200, February 2021, 104312.
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Eremeev A.V., Borisovsky P.A., Kovalenko Y.V., Lysova N.Y., Fomina E.V. Estimation of Physical Performance Level of Man in Long Space Flight Based on Regular Training Data // Proc. of of the 12th International Symposium on Computer Science in Sport (IACSS 2019), Moscow, Russia, Advances in Intelligent Systems and Computing, vol 1028. Springer, Cham. 2020. P. 166-175. Preliminary version available here.
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A. Eremeev and A. Spirov. Evaluation of runtime bounds for SELEX procedure with high selection pressure In: Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion, Prague, Czech Republic, July 13 - 17, 2019. ACM, New York, NY, USA, 2019, pp.113-114. DOI: 10.1145/3319619.3321906.
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A. Eremeev and A. Spirov. Estimates from evolutionary algorithms theory applied to gene design. In: 11th International Multiconference Bioinformatics of Genome Regulation and Structure\Systems Biology (BGRS\SB), IEEE, 2018, pp. 33-38. DOI: 10.1109/CSGB.2018.8544837. Preliminary version available here.
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Alexandre Dolgui, Anton V. Eremeev, Vyatcheslav S. Sigaev, Fitness landscapes of buffer allocation problem for production lines with unreliable machines, Computers and Operations Research, Volume 172, 2024, 106819. Preliminary manuscript available here. Abstract >>>

A.V. Eremeev and A.S. Yurkov. Finding symmetry groups of some quadratic programming problems. Numerical Mathematics: Theory, Methods and Applications. Vol. 16, No. 2, 2023, pp. 370-392.
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C.R.Reeves, A.V.Eremeev, Statistical analysis of local search landscapes. Journal of the Operational Research Society. 55 (7), 2004, pp. 687-693. Abstract >>>

A.V.Eremeev, C.R.Reeves. On confidence intervals for the number of local optima. Applications of Evolutionary Computing: Proceedings of EvoWorkshops. LNCS, Springer, 2003. P. 224-235. © Springer-Verlag. Abstract >>>

A.V.Eremeev, C.R.Reeves Non-parametric Estimation of Properties of Combinatorial Landscapes. In S.Cagnoni et al. (Eds.) Applications of evolutionary computing: Proceedings of EvoWorkshops 2002. LNCS Vol. 2279, 2002. pp. 31-40. © Springer-Verlag. A software implementation of the estimators is available .
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Borisovsky P., Eremeev A., Panin A., Sakhno M. Temporal Bin Packing Problems with Placement Constraints: MIP-Models and Complexity Lecture Notes in Computer Science.2024.V.14766- Mathematical Optimization Theory and Operations Research: Proceedings of 23rd International Conference MOTOR 2024, Omsk, Russia, June 30–July 6, 2024, P.157-169. DOI: 10.1007/978-3-031-62792-7_11
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Eremeev A.V., Kel'manov A.V., Kovalyov M.Y., Pyatkin A.V. Selecting a subset of diverse points based on the squared Euclidean distance. Annals of Mathematics and Artificial Intelligence. 2022. Vol. 90, N 7–9. pp. 965-977. View-only version is available here.
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Eremeev A.V., Kel'manov A.V., Pyatkin A.V. On Complexity of Searching a Subset of Vectors with Shortest Average Under a Cardinality Restriction Proc. of 5th International Conference "Analysis of Images, Social Networks and Texts", AIST 2016, Yekaterinburg, Russia, April 7--9, 2016 / Ed. by D.I.Ignatov, M.Yu.Khachay, V.G.Labunets, N.Loukachevitch, S.I.Nikolenko, A.Panchenko, A.V.Savchenko, K.Vorontsov. Communications in Computer and Information Science. Vol. 661, Springer. 2017. pp.51-57.
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Eremeev A.V., Kel'manov A.V., Pyatkin A.V. On a Quadratic Euclidean Problem of Vector Subset Choice: Complexity and Algorithmic Approach Proc. of 9th International Conference on Discrete Optimization and Operations Research and Scientific School (DOOR 2016), Vladivostok, Russia, September 19 - 23, 2016. CEUR-WS, Vol. 1623, RWTH Aachen University, P. 526-535.
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A.V. Eremeev, A.V. Kel'manov and A.V. Pyatkin On the complexity of some Euclidean optimal summing problems. Doklady Mathematics. V. 93, N 3. 2016. P. 286-288.
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A.V. Eremeev. On Some Approximation Algorithms for Dense Vertex Cover Problem. Proceedings of SOR'99, Springer-Verlag, 2000. pp.58-62. © Springer-Verlag.
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Eremeev A., Zakharova Yu. A restart rule for genetic algorithms based on Schnabel census. Siberian Electronic Mathematical Reports. 2026. Vol. 23, N 1. pp. 554–570.
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Blum C., Eremeev A., Zakharova Yu. Hybridizations of evolutionary algorithms with Large Neighborhood Search. Computer Science Review. 2022. Vol. 46, N 12. pp. 100512-1. Full text.
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Eremeev A.V., Kovalenko Y.V. A memetic algorithm with optimal recombination for the asymmetric travelling salesman problem. Memetic Computing. 12, 2020, pp. 23–36. DOI: 10.1007/s12293-019-00291-4
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A.V. Eremeev. A restarting rule based on the Schnabel Census for genetic algorithms. Proc. of Learning and Intelligent Optimization. (LION 12), Battiti R., Brunato M., Kotsireas I., Pardalos P. (eds) Lecture Notes in Computer Science, vol 11353. Springer, Cham, 2019. P. 337-351. Self-archived version is available here.
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A. Dolgui, A.V. Eremeev, V.S. Sigaev. Analysis of a multicriterial buffer capacity optimization problem for a production line. Autom. Remote Control, 78 (7), 2017, pp. 1276-1289. DOI: 10.1134/S0005117917070098.
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Eremeev A., Kovalenko Yu. Genetic algorithm with optimal recombination for the asymmetric travelling salesman problem. Proc. of The 11th International Conference on Large-Scale Scientific Computations (LSSC-17), June 5 - 9, 2017, Sozopol, Bulgaria. Springer, 2018, LNCS Vol. 10665, pp. 332-339. Self-archived version is available here.
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Guschinskaya O., Gurevsky E., Dolgui A., Eremeev A. Metaheuristic approaches for the design of machining lines. The International Journal of Advanced Manufacturing Technology. Vol. 55, Issue 1-4 (2011), pp. 11-22.
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Dolgui, A., Eremeev, A., Guschinskaya, O. MIP-based GRASP and Genetic algorithm for balancing transfer lines. In: Matheuristics. Hybridizing Metaheuristics and Mathematical Programming, Maniezzo, V., Stutzle, T. and Voss, S. (eds), 2010, Springer, pp. 189-208.
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P. Borisovsky, A. Dolgui, A. Eremeev. Genetic algorithms for a supply management problem: MIP-recombination vs greedy decoder. European Journal of Operational Research, 195 (3) 2009, pp. 770-779. doi:10.1016/j.ejor.2007.06.060. © Elsevier. Accepted authors manuscript.
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A. Dolgui, A.V. Eremeev, V.S. Sigaev. HBBA: hybrid algorithm for buffer allocation in tandem production lines. Journal of Intelligent Manufacturing. 18 (3), 2007, pp. 411-420. The original publication is available at www.springerlink.com. DOI 10.1007/s10845-007-0030-z.
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Dolgui A., Eremeev A., Kolokolov A., Sigaev V. A Genetic Algorithm for the Allocation of Buffer Storage Capacities in a Production Line with Unreliable Machines. Journal of Mathematical Modelling and Algorithms. 1 (2), 2002, pp. 89-104.
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A.V. Eremeev, A.A.Kolokolov, L.A.Zaozerskaya. A Hybrid Algorithm for Set Covering Problem Proc. of International Workshop "Discrete Optimization Methods in Scheduling and Computer-Aided Design". Minsk, Belarus, 2000. pp.123-129.
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A.V. Eremeev. A Genetic Algorithm with a Non-Binary Representation for the Set Covering Problem. In Proceedings of OR'98, Springer-Verlag, 175-181, 1999. © Springer-Verlag. An updated version is available.
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A.V. Eremeev, A.A.Kolokolov. An Application of Genetic Algorithm and L-class Enumeration to the Integer Programming Problem. In Proc. of The 1st Online Workshop on Soft Computing, Nagoya, 1996.

A.V.Eremeev, A.A.Kolokolov. On Some Genetic and L-class Enumeration Algorithms in Integer Programming. In Proceedings of the First International Conference on Evolutionary Computation and Its Applications. Moscow, Russia. 1996, pp.297-303.
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A. Eremeev, A. Gette, S. Hrushev and T. Levanova, Location and Design of Ground Stations for Software Defined Satellite Networks. In Proc. of 2022 Dynamics of Systems, Mechanisms and Machines (Dynamics), Omsk, Russian Federation, 2022, pp. 1-4. Full text.
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Borisovsky P., Eremeev A., Kovalenko Y., Zaozerskaya L. (2021) Rig Routing with Possible Returns and Stochastic Drilling Times. In: Pardalos P., Khachay M., Kazakov A. (eds) Mathematical Optimization Theory and Operations Research. MOTOR 2021. Lecture Notes in Computer Science, vol 12755. Springer, Cham. pp. 51-66. A self-archived version is available here.
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Eremeev A.V., Malakhov A.A., Sakhno M.A., Sosnovskaya M.Y. (2020) Multi-core Processor Scheduling with Respect to Data Bus Bandwidth. In: Olenev N., Evtushenko Y., Khachay M., Malkova V. (eds) Advances in Optimization and Applications. OPTIMA 2020. Communications in Computer and Information Science, vol 1340. Springer, Cham, pp. 55-69. A preprint is available here.
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Borisovsky P., Eremeev A., Kallrath J. Multi-product continuous plant scheduling: combination of decomposition, genetic algorithm, and constructive heuristic. International Journal of Production Research, published online, 2019. (DOI: 10.1080/00207543.2019.1630764) Abstract >>>

Borisovsky P., Eremeev A., Hrushev S., Teplyakov V., Vorozhtsov M. On three approaches to length-bounded maximum multicommodity flow with unit edge-lengths. Yugoslav Journal of Operations Research, Vol. 29, N 1, 93-112 (2019) (DOI: 10.2298/YJOR181015034B) Abstract >>>

A. V. Eremeev, M. Y. Kovalyov, P. M. Kuznetsov Lot-size scheduling of a single product on unrelated parallel machines. Optimization Letters, 14, 2020, pp. 557–568. DOI: 10.1007/s11590-018-1307-1 Original manuscript.
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A. V. Eremeev, M. Y. Kovalyov, P. M. Kuznetsov Single product lot-sizing on unrelated parallel machines with nondecreasing processing times. Journal of Physics: Conference Series, Vol. 944, N 1, IOP Publishing Ltd, 2018, 7 pages.
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Dolgui, A.B., Eremeev, A.V., Kovalyov, M.Y., Sigaev, V.S. (2018). Complexity of Bi-objective Buffer Allocation Problem in Systems with Simple Structure. In: Eremeev, A., Khachay, M., Kochetov, Y., Pardalos, P. (eds) Optimization Problems and Their Applications. OPTA 2018. Communications in Computer and Information Science, vol 871. Springer, Cham. pp. 278–287. The final publication is available at www.springerlink.com. A self-archived version is available here.
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Eremeev A., Kovalenko Yu. On Solving Travelling Salesman Problem with Vertex Requisitions. Yugoslav Journal of Operations Research, Vol. 27, N 4, 413-424 (2017) (DOI: 10.2298/YJOR161012003E)
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Eremeev A., Kovalenko Yu. Mixed integer programming approach to multiprocessor job scheduling with setup times. In Proc. of 9th International Conference "Discrete Optimization and Operations Research" (DOOR 2016), Vladivostok, Russia, September 19-23, 2016, LNCS Vo. 9869, Springer, 2016, P.298-306. © Springer-Verlag. The original publication is available here.
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A.V. Eremeev, J.V. Kovalenko On multi-product lot-sizing and scheduling with multi-machine technologies. In: Operations Research Proceedings 2014. Selected Papers of the Annual International Conference of the German Operations Research Society (GOR), (September 2-5, 2014), 2016, Springer, pp. 301-306. © Springer-Verlag. The original publication is available here.
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P. Borisovsky, A. V. Eremeev, J. Kallrath. Reducing the number of changeover constraints in a MIP formulation of a continuous-time scheduling problem. Proc. of VIII International School-Symposium "Analysis, Modelling, Management and Development of Economical Systems" (AMUR-2014). - Sevastopol, Russia, 2014, pp. 46-50. Preprint available as arXiv:1408.5832v1.
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A. Dolgui, A.V. Eremeev, M.Y. Kovalyov and V.S. Sigaev. Complexity of buffer capacity allocation problems for production lines with unreliable machines. Journal of Mathematical Modelling and Algorithms in Operations Research, 12 (2), 2013, pp.155-165. The final publication is available at www.springerlink.com. A self-archived version is available here.
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A. Dolgui, A. V. Eremeev, M. Y. Kovalyov, P. M. Kuznetsov Multi-product lot sizing and scheduling on unrelated parallel machines. IIE Transactions. 2010, 42 (7) pp. 514 - 524.
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A. V. Eremeev, M. Ya. Kovalyov and P. M. Kuznetsov. Approximate solution of the control problem of supplies with many intervals and concave cost functions. Automation and Remote Control. 2008, 69 (7) pp. 1181-1187 © MAIK Nauka. DOI: 10.1134/S0005117908070096. Download preliminary version in Russian.
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A. Dolgui, A. Eremeev, M. Kovalyov. Multi-product lot-sizing and scheduling on unrelated parallel machines. Research Report 2007-500-011, Ecole des Mines de Saint-Etienne, France, 2007, 15p.
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S.S. Chauhan, A.V. Eremeev, A.A. Romanova, V.V.Servakh. Approximation of linear cost supply management problem with lower-bounded demands. Proceedings of Discrete Optimization Methods in Production and Logistics (DOM'2004). Omsk. Nasledie Dialog-Sibir Pbs., 2004. pp. 16-21.
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S.S. Chauhan, A.V. Eremeev, A.A.Kolokolov, V.V.Servakh. Concave cost supply management problem for single manufacturing unit. In: Supply Chain Optimisation, Product/Process Design, Facility Location and Flow Control. Ed. by A. Dolgui, J. Soldek, O. Zaikin. Series : Applied Optimization, Vol. 94, 2005. Springer Verlag, pp. 167-174.
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A.V. Eremeev. On computational complexity of the electric power flow optimization problem in market environment. Journal of Applied and Industrial Mathematics. 2017, Vol. 11, Issue 4, - P. 500-505.
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P.A. Borisovsky, A.V. Eremeev, E.B. Grinkevich, S.A. Klokov and N.A. Kosarev. Trading hubs construction in electricity markets using evolutionary algorithms. Pattern Recognition and Image Analysis. 2014, Vol. 24, Issue 2, - P. 270-282.

This is a preprint of the paper accepted to journal Pattern Recognition and Image Analysis © Pleiades Publishing, Ltd., 2014.
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P.A. Borisovsky, A.V. Eremeev, E.B. Grinkevich, S.A. Klokov and A.V. Vinnikov Trading hubs construction for electricity markets. In: Optimization in the Energy Industry. J. Kallrath, P.M. Pardalos, S. Rebennack, M. Scheidt (Eds.), 2009, Springer, - P. 29-58.
The original publication is available at www.springerlink.com..
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