Skip to main content

Advertisement

Log in

An improved subgradient extragradient method with two different parameters for solving variational inequalities in reflexive Banach spaces

  • Published:
Computational and Applied Mathematics Aims and scope Submit manuscript

Abstract

In this paper, we combine the classical subgradient extragradient method with the Bregman projection method for solving variational inequality problems in reflexive Banach spaces. Specifically, we set two different parameters in the two-step projections, as opposed to consistent parameters in other results. In addition, the application of the inertial technique accelerates the iteration efficiency. Finally, we compare the proposed algorithm with other known results and find that our method effectively improves the convergence process.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

References

  • Abass HA, Godwin GC, Narain OK, Darvish V (2022) Inertial extragradient method for solving variational inequality and fixed point problems of a Bregman demigeneralized mapping in a reflexive Banach spaces. Numer Funct Anal Optim 43:933–960

    Article  MathSciNet  MATH  Google Scholar 

  • Abubakar J, Kumam P, Rehman HU (2022) Self-adaptive inertial subgradient extragradient scheme for pseudomonotone variational inequality problem. Int J Nonlinear Sci Numer Simul 23:77–96

    Article  MathSciNet  MATH  Google Scholar 

  • Alber YI (1996) Metric and generalized projection operators in Banach spaces: properties and applications. Theory and applications of nonlinear operators of accretive and monotone type, Lecture Notes in Pure and Appl. Math., vol 178. Dekker, New York, pp 15–50

    Google Scholar 

  • Barbagallo A, Di Vincenzo R (2015) Evolutionary variational inequality with long-term memory and applications to economic networks. Optim. Methods Softw. 30:253–275

    Article  MathSciNet  MATH  Google Scholar 

  • Butnariu D, Iusem AN (2000) Totally convex functions for fixed points computation and infinite dimensional optimization. Applied Optimization, vol 40. Kluwer Academic Publishers, Dordrecht

    MATH  Google Scholar 

  • Cai G, Gibali A, Iyiola OS, Shehu Y (2018) A new double-projection method for solving variational inequalities in Banach spaces. J Optim Theory Appl 178:219–239

    Article  MathSciNet  MATH  Google Scholar 

  • Ceng LC, Petrusel A, Yao JC (2014) Composite viscosity approximation methods for equilibrium problem, variational inequality and common fixed points. J Nonlinear Convex Anal 15:219–240

    MathSciNet  MATH  Google Scholar 

  • Censor Y, Lent A (1981) An iterative row-action method for interval convex programming. J Optim Theory Appl 34:321–353

    Article  MathSciNet  MATH  Google Scholar 

  • Censor Y, Gibali A, Reich S (2011) The subgradient extragradient method for solving variational inequalities in Hilbert space. J Optim Theory Appl 148:318–335

    Article  MathSciNet  MATH  Google Scholar 

  • Dong QL, Lu YY, Yang J (2016) The extragradient algorithm with inertial effects for solving the variational inequality. Optimization 65:2217–2226

    Article  MathSciNet  MATH  Google Scholar 

  • Hieu DV, Cho YJ, Xiao Y, Kumam P (2020) Relaxed extragradient algorithm for solving pseudomonotone variational inequalities in Hilbert spaces. Optimization 69:2279–304

    Article  MathSciNet  MATH  Google Scholar 

  • Jitpeera T, Kumam P (2010) An extragradient type method for a system of equilibrium problems, variational inequality problems and fixed points of finitely many nonexpansive mappings. J Nonlinear Anal Optim 1:71–91

    MathSciNet  MATH  Google Scholar 

  • Jolaoso LO, Shehu Y (2022) Single Bregman projection method for solving variational inequalities in reflexive Banach spaces. Appl Anal 101:4807–4828

    Article  MathSciNet  MATH  Google Scholar 

  • Jolaoso LO, Qin X, Shehu Y, Yao JC (2021) Improved subgradient extragradient methods with self-adaptive stepsizes for variational inequalities in Hilbert spaces. J Nonlinear Convex Anal 22:1591–1614

    MathSciNet  MATH  Google Scholar 

  • Jolaoso LO, Oyewole OK, Aremu KO (2022) A Bregman subgradient extragradient method with self-adaptive technique for solving variational inequalities in reflexive Banach spaces. Optimization 71:3835–3860

    Article  MathSciNet  MATH  Google Scholar 

  • Korpelevich GM (1976) The extragradient method for finding saddle points and other problems. Ekon Mat Metod 12:747–756

    MathSciNet  MATH  Google Scholar 

  • Kraikaew R, Saejung S (2014) Strong convergence of the Halpern subgradient extragradient method for solving variational inequalities in Hilbert spaces. J Optim Theory Appl 163:399–412

    Article  MathSciNet  MATH  Google Scholar 

  • Lions JL (1977) Numerical methods for variational inequalities-applications in physics and in control theory. Inf Process 77:917–924

    MathSciNet  Google Scholar 

  • Maingé PE (2008) Strong convergence of projected subgradient methods for nonsmooth and nonstrictly convex minimization. Set-Val Anal 16:899–912

    Article  MathSciNet  MATH  Google Scholar 

  • Martín-Márquez V, Reich S, Sabach S (2013) Bregman strongly nonexpansive operators in reflexive Banach spaces. J Math Anal Appl 400:597–614

    Article  MathSciNet  MATH  Google Scholar 

  • Mashreghi J, Nasri M (2010) Forcing strong convergence of Korpelevich’s method in Banach spaces with its applications in game theory. Nonlinear Anal 72:2086–2099

    Article  MathSciNet  MATH  Google Scholar 

  • Naraghirad E, Yao JC (2013) Bregman weak relatively nonexpansive mappings in Banach spaces. Fixed Point Theory Appl 141:43

    MathSciNet  MATH  Google Scholar 

  • Oyewole OK, Jolaoso LO, Aremu KO, Olayiwola MO (2022) Inertial self-adaptive Bregman projection method for finite family of variational inequality problems in reflexive Banach spaces. Comput Appl Math 41:22

    Article  MathSciNet  MATH  Google Scholar 

  • Phelps RR (1993) Convex functions, monotone operators and differentiability. Lecture Notes in Mathematics, vol 1364, 2nd edn. Springer, Berlin

    Google Scholar 

  • Popov LD (1980) A modification of the Arrow-Hurwitz method of search for saddle points. Mat Zamet 28:777–784

    MathSciNet  MATH  Google Scholar 

  • Reich S, Sabach S (2009) A strong convergence theorem for a proximal-type algorithm in reflexive Banach spaces. J Nonlinear Convex Anal 10:471–485

    MathSciNet  MATH  Google Scholar 

  • Reich S, Tuyen TM, Sunthrayuth P, Cholamjiak P (2021) Two new inertial algorithms for solving variational inequalities in reflexive Banach spaces. Numer Funct Anal Optim 42:1954–1984

    Article  MathSciNet  MATH  Google Scholar 

  • Tan B, Liu L, Qin X (2022) Strong convergence of inertial extragradient algorithms for solving variational inequalities and fixed point problems. Fixed Point Theory 23:707–727

    Article  MathSciNet  Google Scholar 

  • Thong DV, Hieu DV (2018) Modified subgradient extragradient method for variational inequality problems. Numer Algorithms 79:597–610

    Article  MathSciNet  MATH  Google Scholar 

  • Tseng P (2000) A modified forward-backward splitting method for maximal monotone mappings. SIAM J Control Optim 38:431–446

    Article  MathSciNet  MATH  Google Scholar 

  • Xie Z, Cai G, Li X, Dong QL (2021) Strong convergence of the modified inertial extragradient method with line-search process for solving variational inequality problems in Hilbert spaces. J Sci Comput 88:19

    Article  MathSciNet  MATH  Google Scholar 

  • Xie Z, Cai G, Dong QL (2023) Strong convergence of Bregman projection method for solving variational inequality problems in reflexive Banach spaces. Numer Algorithms 93:269–294

    Article  MathSciNet  MATH  Google Scholar 

  • Xu HK (2002) Iterative algorithms for nonlinear operators. J Lond Math Soc 66:240–256

    Article  MathSciNet  MATH  Google Scholar 

  • Yang J, Liu H, Li G (2020) Convergence of a subgradient extragradient algorithm for solving monotone variational inequalities. Numer Algorithms 84:389–405

    Article  MathSciNet  MATH  Google Scholar 

  • Yao Y, Liou YC, Yao JC (2011) New relaxed hybrid-extragradient method for fixed point problems, a general system of variational inequality problems and generalized mixed equilibrium problems. Optimization 60:395–412

    Article  MathSciNet  MATH  Google Scholar 

  • Yao Y, Postolache M, Yao JC (2020) Strong convergence of an extragradient algorithm for variational inequality and fixed point problems. Politehn Univ Buchar Sci Bull Ser A Appl Math Phys. 82:3–12

    MathSciNet  MATH  Google Scholar 

  • Yao Y, Iyiola OS, Shehu Y (2022) Subgradient extragradient method with double inertial steps for variational inequalities. J Sci Comput 90:29

    Article  MathSciNet  MATH  Google Scholar 

  • Zâlinescu C (2002) Convex analysis in general vector spaces. World Scientific Publishing, Singapore

    Book  MATH  Google Scholar 

Download references

Acknowledgements

This work was supported by the NSF of China (Grant no. 12171062).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhongbing Xie.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, H., Xie, Z. & Li, M. An improved subgradient extragradient method with two different parameters for solving variational inequalities in reflexive Banach spaces. Comp. Appl. Math. 42, 254 (2023). https://doi.org/10.1007/s40314-023-02394-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s40314-023-02394-8

Keywords

Mathematics Subject Classification

Navigation