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Publications in Math-Net.Ru
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Equivalence relations in convex optimization
Diskretn. Anal. Issled. Oper., 30:2 (2023), 81–90
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A Bicomposition of Conical Projections
Trudy Inst. Mat. i Mekh. UrO RAN, 29:3 (2023), 73–87
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Modeling and optimizing large-scale production-level transportation systems
Diskretn. Anal. Issled. Oper., 29:3 (2022), 64–84
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Neural network analysis of transportation flows of urban aglomeration using the data from public video cameras
Computer Research and Modeling, 13:2 (2021), 305–318
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The Walrasian equilibrium and centralized distributed optimization in terms of modern convex optimization methods on the example of resource allocation problem
Sib. Zh. Vychisl. Mat., 22:4 (2019), 415–436
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Method of conjugate subgradients with constrained memory
Avtomat. i Telemekh., 2014, no. 4, 67–80
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The Parker–Sochacki method for solving systems of ordinary differential equations using graphics processors
Sib. Zh. Vychisl. Mat., 14:3 (2011), 277–289
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Fejer algorithms with an adaptive step
Zh. Vychisl. Mat. Mat. Fiz., 51:5 (2011), 791–801
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The use of additional diminishing disturbances in Fejer models of iterative algorithms
Zh. Vychisl. Mat. Mat. Fiz., 48:12 (2008), 2121–2128
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Projection onto polyhedra in outer representation
Zh. Vychisl. Mat. Mat. Fiz., 48:3 (2008), 387–396
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A method of local convex majorants for solving variational-like inequalities
Zh. Vychisl. Mat. Mat. Fiz., 47:3 (2007), 355–363
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An accelerated parallel projection method for solving the minimum length problem
Num. Meth. Prog., 7:3 (2006), 273–277
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A separating plane algorithm with limited memory for convex nonsmooth optimization
Num. Meth. Prog., 7:1 (2006), 133–137
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Convergence of the suitable affine subspace method for finding the least distance to a simplex
Zh. Vychisl. Mat. Mat. Fiz., 45:11 (2005), 1991–1999
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Portfolio replication: its forward-dual decomposition
Avtomat. i Telemekh., 2004, no. 2, 170–178
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A parallel method of projection onto the convex hull of a family of sets
Izv. Vyssh. Uchebn. Zaved. Mat., 2003, no. 12, 78–82
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Numerical experiments in a new class of algorithms in linear programming
Zh. Vychisl. Mat. Mat. Fiz., 27:3 (1987), 349–356
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A class of convex programming methods
Zh. Vychisl. Mat. Mat. Fiz., 26:8 (1986), 1150–1159
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Автомобильные пробки: когда рациональность ведет к коллапсу
Kvant, 2013, no. 1, 13–18
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Mathematical Programming: State of the Art
Avtomat. i Telemekh., 2012, no. 2, 3–4
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