Zhadan Vitalii Grigor'evich

Publications in Math-Net.Ru

1. Primal–dual Newton method with steepest descent for the linear semidefinite programming problem: iterative process
   
   Zh. Vychisl. Mat. Mat. Fiz., 62:4 (2022),  597–615
2. Primal–dual Newton method with steepest descent for the linear semidefinite programming problem: Newton's system of equations
   
   Zh. Vychisl. Mat. Mat. Fiz., 62:2 (2022),  232–248
3. Primal Newton method for the linear cone programming problem
   
   Zh. Vychisl. Mat. Mat. Fiz., 58:2 (2018),  220–227
4. A variant of the affine-scaling method for a cone programming problem on a second-order cone
   
   Trudy Inst. Mat. i Mekh. UrO RAN, 23:3 (2017),  114–124
5. A variant of the dual simplex method for a linear semidefinite programming problem
   
   Trudy Inst. Mat. i Mekh. UrO RAN, 22:3 (2016),  90–100
6. A feasible dual affine scaling steepest descent method for the linear semidefinite programming problem
   
   Zh. Vychisl. Mat. Mat. Fiz., 56:7 (2016),  1248–1266
7. On a variant of the simplex method for a linear semidefinite programming problem
   
   Trudy Inst. Mat. i Mekh. UrO RAN, 21:3 (2015),  117–127
8. On a variant of a feasible affine scaling method for semidefinite programming
   
   Trudy Inst. Mat. i Mekh. UrO RAN, 20:2 (2014),  145–160
9. Primal-dual Newton method for a linear problem of semidefinite programming
   
   Trudy Inst. Mat. i Mekh. UrO RAN, 19:2 (2013),  157–169
10. An admissible dual internal point method for a linear semidefinite programming problem
    
    Avtomat. i Telemekh., 2012, no. 2,  25–40
11. On convergence of the dual Newton method for linear semidefinite programming problem
    
    Bulletin of Irkutsk State University. Series Mathematics, 4:2 (2011),  75–90
12. Dual interior point methods for linear semidefinite programming problems
    
    Zh. Vychisl. Mat. Mat. Fiz., 51:12 (2011),  2158–2180
13. Direct newton method for a linear problem of semidefinite programming
    
    Trudy Inst. Mat. i Mekh. UrO RAN, 14:2 (2008),  67–80
14. A primal interior point method for the linear semidefinite programming problem
    
    Zh. Vychisl. Mat. Mat. Fiz., 48:10 (2008),  1780–1801
15. The steepest-descent barrier-projection method for linear complementarity problems
    
    Zh. Vychisl. Mat. Mat. Fiz., 45:5 (2005),  792–812
16. Convergence of the primal-dual Newton method for linear programming problems
    
    Zh. Vychisl. Mat. Mat. Fiz., 39:3 (1999),  431–445
17. Primal-dual Newton method for linear programming problems
    
    Zh. Vychisl. Mat. Mat. Fiz., 39:1 (1999),  17–32
18. Dual barrier-projection and barrier-Newton methods for linear programming problems
    
    Zh. Vychisl. Mat. Mat. Fiz., 36:7 (1996),  30–45
19. The use of Newton's method for linear programming
    
    Zh. Vychisl. Mat. Mat. Fiz., 35:6 (1995),  850–866
20. Barrier-projective methods for nonlinear programming
    
    Zh. Vychisl. Mat. Mat. Fiz., 34:5 (1994),  669–684
21. Exact auxiliary functions in optimization problems
    
    Zh. Vychisl. Mat. Mat. Fiz., 30:1 (1990),  43–57
22. An augmented Lagrange function method for multicriterion optimization problems
    
    Zh. Vychisl. Mat. Mat. Fiz., 28:11 (1988),  1603–1618
23. Method of feasible directions for solving problems of convex multicriterion optimization
    
    Zh. Vychisl. Mat. Mat. Fiz., 27:6 (1987),  829–838
24. A method for the parametric representation of objective functions in conditional multicriterial optimization
    
    Zh. Vychisl. Mat. Mat. Fiz., 26:2 (1986),  177–189
25. On some estimates of the penalty coefficient in methods of exact penalty functions
    
    Zh. Vychisl. Mat. Mat. Fiz., 24:8 (1984),  1164–1171
26. A class of iterative methods of solution of convex programming problems
    
    Zh. Vychisl. Mat. Mat. Fiz., 24:5 (1984),  665–676
27. Two modifications of the linearization method in nonlinear programming
    
    Zh. Vychisl. Mat. Mat. Fiz., 23:2 (1983),  314–325
28. Modified Lagrangian functions in nonlinear programming
    
    Zh. Vychisl. Mat. Mat. Fiz., 22:2 (1982),  296–308
29. On two classes of methods of solving nonlinear programming problems
    
    Dokl. Akad. Nauk SSSR, 254:3 (1980),  531–534
30. Iterative methods for solving non-linear programming problems, using modified Lagrange functions
    
    Zh. Vychisl. Mat. Mat. Fiz., 20:4 (1980),  874–888
31. A relaxation method for solving problems of non-linear programming
    
    Zh. Vychisl. Mat. Mat. Fiz., 17:4 (1977),  890–904
32. An application of the method of Ljapunov functions to the study of the convergence of numerical methods
    
    Zh. Vychisl. Mat. Mat. Fiz., 15:1 (1975),  101–112
33. Numerical methods of solving some operational research problems
    
    Zh. Vychisl. Mat. Mat. Fiz., 13:3 (1973),  583–598


34. Letter to the editor: Concerning some publications on internal point methods
    
    Zh. Vychisl. Mat. Mat. Fiz., 36:12 (1996),  161–162