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A VISCOSITY TYPE PROJECTION METHOD FOR SOLVING PSEUDOMONOTONE VARIATIONAL INEQUALITIES

  • Muangchoo, Kanikar (Department of Mathematics and Statistics, Faculty of Science and Technology Rajamangala University of Technology Phra Nakhon (RMUTP))
  • Received : 2020.09.28
  • Accepted : 2021.03.31
  • Published : 2021.06.15

Abstract

A plethora of applications from mathematical programmings, such as minimax, mathematical programming, penalization and fixed point problems can be framed as variational inequality problems. Most of the methods that used to solve such problems involve iterative methods, that is why, in this paper, we introduce a new extragradient-like method to solve pseudomonotone variational inequalities in a real Hilbert space. The proposed method has the advantage of a variable step size rule that is updated for each iteration based on previous iterations. The main advantage of this method is that it operates without the previous knowledge of the Lipschitz constants of an operator. A strong convergence theorem for the proposed method is proved by letting the mild conditions on an operator 𝒢. Numerical experiments have been studied in order to validate the numerical performance of the proposed method and to compare it with existing methods.

Keywords

Acknowledgement

This project was supported by Rajamangala University of Technology Phra Nakhon (RMUTP).

References

  1. M.O. Aibinu and J.K. Kim, Convergence analysis of viscosity implicit rules of nonexpansive mappings in Banach spaces, Nonlinear Funct. Anal. Appl., 24(4) (2019), 691-713.
  2. M.O. Aibinu and J.K. Kim, On the rate of convergence of viscosity implicit iterative algorithms, Nonlinear Funct. Anal. Appl., 25(1) (2020), 135-152.
  3. A.S. Antipin, On a method for convex programs using a symmetrical modification of the Lagrange function, Ekonomika i Matematicheskie Metody, 12(6) (1976), 1164-1173.
  4. H.H. Bauschke and P.L. Combettes, Convex analysis and monotone operator theory in Hilbert spaces, Springer, New York, 2011.
  5. Y. Censor, A. Gibali and S. Reich, The subgradient extragradient method for solving variational inequalities in Hilbert space, J. Optim. Theory Appl., 148(2) (2010), 318-335. https://doi.org/10.1007/s10957-010-9757-3
  6. Y. Censor, A. Gibali and S. Reich, Extensions of korpelevich extragradient method for the variational inequality problem in euclidean space, Optim., 61(9) (2012), 1119-1132. https://doi.org/10.1080/02331934.2010.539689
  7. Q.L. Dong, Y.J. Cho, L.L. Zhong and T.M. Rassias, Inertial projection and contraction algorithms for variational inequalities, J. Global Optim., 70(3) (2017), 687-704. https://doi.org/10.1007/s10898-017-0506-0
  8. C.M. Elliott, Variational and Quasivariational Inequalities Applications to Free-Boundary Problems.(Claudio Baiocchi And Antonio Capelo), SIAM Rev., 29(2) (1987), 314-315. https://doi.org/10.1137/1029059
  9. P.T. Harker and J.-S. Pang, for the linear complementarity problem, Lectures in Applied Mathematics, 26 (1990).
  10. D.V. Hieu, P.K. Anh and L.D. Muu, Modified hybrid projection methods for finding common solutions to variational inequality problems, Comput. Optim. Appl., 66(1) (2016), 75-96. https://doi.org/10.1007/s10589-016-9857-6
  11. X. Hu and J. Wang, Solving pseudomonotone variational inequalities and pseudoconvex optimization problems using the projection neural network, IEEE Trans. Neural Networks, 17(6) (2006), 1487-1499. https://doi.org/10.1109/TNN.2006.879774
  12. A.N. Iusem and B.F. Svaiter, A variant of Korpelevich's method for variational inequalities with a new search strategy, Optim., 42(4) (1997), 309-321. https://doi.org/10.1080/02331939708844365
  13. G. Kassay, J. Kolumban and Z. Pales. On Nash stationary points, Publ. Math., 54(3-4) (1999), 267-279.
  14. G. Kassay, J. Kolumban and Z. Pales, Factorization of minty and Stampacchia variational inequality systems, Eur. J. Oper. Res., 143(2) (2002), 377-389. https://doi.org/10.1016/S0377-2217(02)00290-4
  15. J.K. Kim, A.H. Dar and Salahuddin, Existence theorems for the generalized relaxed pseudomonotone variational inequalities Nonlinear Funct. Anal. Appl., 25(1) (2020), 25-34.
  16. D. Kinderlehrer and G. Stampacchia, An introduction to variational inequalities and their applications, Academic Press, New York and London, 1980.
  17. I. Konnov, Equilibrium models and variational inequalities, Elsevier, New York, 2007.
  18. G. Korpelevich, The extragradient method for finding saddle points and other problems, Matecon, 12 (1976), 747-756.
  19. R. Kraikaew and S. Saejung, Strong convergence of the Halpern subgradient extragradient method for solving variational inequalities in Hilbert spaces, J. Optim. Theory Appl., 163(2) (2013), 399-412. https://doi.org/10.1007/s10957-013-0494-2
  20. E. Kreyszig, Introductory Functional Analysis with Applications, Wiley Classics Library, New York, 1989.
  21. Z. Liu, S. Mig'orski and S. Zeng, Partial differential variational inequalities involving nonlocal boundary conditions in Banach spaces, J. Differ. Equ., 263(7) (2017), 3989-4006. https://doi.org/10.1016/j.jde.2017.05.010
  22. Z. Liu, S. Zeng and D. Motreanu, Evolutionary problems driven by variational inequalities, J. Differ. Equ., 260(9) (216), 6787-6799. https://doi.org/10.1016/j.jde.2016.01.012
  23. P.-E. Mainge, Strong convergence of projected subgradient methods for nonsmooth and nonstrictly convex minimization, Set-Valued Anal., 16(7-8) (2008), 899-912. https://doi.org/10.1007/s11228-008-0102-z
  24. Y.V. Malitsky and V.V. Semenov, An extragradient algorithm for monotone variational inequalities, Cybern. Syst. Anal., 50(2) (2014), 271-277. https://doi.org/10.1007/s10559-014-9614-8
  25. A.A. Mogbademu, New iteration process for a general class of contractive mappings, Acta Comment. Univ. Tartu. Math., 20(2) (2016), 117-122.
  26. A. Moudafi, Viscosity approximation methods for fixed-points problems, J. Math. Anal. Appl., 241(1) (2000), 46-55. https://doi.org/10.1006/jmaa.1999.6615
  27. A. Nagurney, A variational inequality approach, Springer, Dordrecht, Boston, 1999.
  28. M.A. Noor, General variational inequalities, Appl. Math. Lett., 1(2) (1988), 119-122. https://doi.org/10.1016/0893-9659(88)90054-7
  29. M.A. Noor, An iterative algorithm for variational inequalities, J. Math. Anal. Appl., 158(2) (1991), 448-455. https://doi.org/10.1016/0022-247x(91)90248-x
  30. M.A. Noor, Some iterative methods for nonconvex variational inequalities, Comput. Math. Model., 21(1) (2010), 97-108. https://doi.org/10.1007/s10598-010-9057-7
  31. Y. Shehu, Q.-L. Dong and D. Jiang, Single projection method for pseudo-monotone variational inequality in Hilbert spaces, Optim., 68(1) (2018), 385-409. https://doi.org/10.1080/02331934.2018.1522636
  32. M.V. Solodov and B.F. Svaiter, A new projection method for variational inequality problems, SIAM J. Control Optim., 37(3) (1999), 765-776. https://doi.org/10.1137/S0363012997317475
  33. G. Stampacchia, Formes bilin'eaires coercitives sur les ensembles convexes, Comptes Rendus Hebdomadaires Des Seances De L Academie Des Sciences, 258(18) (1964), 4413-4416.
  34. W. Takahashi, Nonlinear functional analysis, Yokohama Publishers, Yokohama, 2000.
  35. W. Takahashi, Introduction to nonlinear and convex analysis, Yokohama Publishers, Yokohama, 2009.
  36. D.V. Thong and D.V. Hieu, Modified subgradient extragradient method for variational inequality problems, Numer. Algorithms, 79(2) (2017), 597-610. https://doi.org/10.1007/s11075-017-0452-4
  37. D.V. Thong and D.V. Hieu, Weak and strong convergence theorems for variational inequality problems, Numer. Algorithms, 78(4) (2017), 1045-1060. https://doi.org/10.1007/s11075-017-0412-z
  38. P. Tseng, A modified forward-backward splitting method for maximal monotone mappings, SIAM J. Control Optim., 38(2) (2000), 431-446. https://doi.org/10.1137/S0363012998338806
  39. D.V. Hieu, P.K. Anh and L.D. Muu, Modified hybrid projection methods for finding common solutions to variational inequality problems, Comput. Optim. Appl., 66(1) (2017), 75-96. https://doi.org/10.1007/s10589-016-9857-6
  40. H.K. Xu, Another control condition in an iterative method for nonexpansive mappings, Bull. Aust. Math. Soc., 65(1) (2002), 109-113. https://doi.org/10.1017/S0004972700020116
  41. J. Yang, H. Liu and Z. Liu, Modified subgradient extragradient algorithms for solving monotone variational inequalities, Optim., 67(12) (2018), 2247-2258. https://doi.org/10.1080/02331934.2018.1523404
  42. L. Zhang, C. Fang and S. Chen, An inertial subgradient-type method for solving single-valued variational inequalities and fixed point problems, Numer. Algorithms, 79(3) (2018), 941-956. https://doi.org/10.1007/s11075-017-0468-9