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Strong convergence results for quasimonotone variational inequalities

Author

Listed:
  • Timilehin O. Alakoya

    (University of KwaZulu-Natal)

  • Oluwatosin T. Mewomo

    (University of KwaZulu-Natal)

  • Yekini Shehu

    (Zhejiang Normal University)

Abstract

A survey of the existing literature reveals that results on quasimonotone variational inequality problems are scanty in the literature. Moreover, the few existing results are either obtained in finite dimensional Hilbert spaces or the authors were only able to obtain weak convergence results in infinite dimensional Hilbert spaces. In this paper, we study the quasimonotone variational inequality problem and variational inequality problem without monotonicity. We introduce two new inertial iterative schemes with self-adaptive step sizes for approximating a solution of the variational inequality problem. Our proposed methods combine the inertial Tseng extragradient method with viscosity approximation method. We prove some strong convergence results for the proposed algorithms without the knowledge of the Lipschitz constant of the cost operator in infinite dimensional Hilbert spaces. Finally, we provide some numerical experiments to demonstrate the efficiency of our proposed methods in comparison with some recently announced results in the literature in this direction.

Suggested Citation

  • Timilehin O. Alakoya & Oluwatosin T. Mewomo & Yekini Shehu, 2022. "Strong convergence results for quasimonotone variational inequalities," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 95(2), pages 249-279, April.
    • Handle: RePEc:spr:mathme:v:95:y:2022:i:2:d:10.1007_s00186-022-00780-2
    DOI: 10.1007/s00186-022-00780-2
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    References listed on IDEAS

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    1. Lateef Olakunle Jolaoso & Adeolu Taiwo & Timilehin Opeyemi Alakoya & Oluwatosin Temitope Mewomo, 2020. "A Strong Convergence Theorem for Solving Pseudo-monotone Variational Inequalities Using Projection Methods," Journal of Optimization Theory and Applications, Springer, vol. 185(3), pages 744-766, June.
    2. Rapeepan Kraikaew & Satit Saejung, 2014. "Strong Convergence of the Halpern Subgradient Extragradient Method for Solving Variational Inequalities in Hilbert Spaces," Journal of Optimization Theory and Applications, Springer, vol. 163(2), pages 399-412, November.
    3. Bing Tan & Shanshan Xu & Songxiao Li, 2020. "Modified Inertial Hybrid and Shrinking Projection Algorithms for Solving Fixed Point Problems," Mathematics, MDPI, vol. 8(2), pages 1-12, February.
    4. Y. Censor & A. Gibali & S. Reich, 2011. "The Subgradient Extragradient Method for Solving Variational Inequalities in Hilbert Space," Journal of Optimization Theory and Applications, Springer, vol. 148(2), pages 318-335, February.
    5. Dang Hieu & Pham Ky Anh & Le Dung Muu, 2017. "Modified hybrid projection methods for finding common solutions to variational inequality problems," Computational Optimization and Applications, Springer, vol. 66(1), pages 75-96, January.
    6. Minglu Ye & Yiran He, 2015. "A double projection method for solving variational inequalities without monotonicity," Computational Optimization and Applications, Springer, vol. 60(1), pages 141-150, January.
    7. Hongwei Liu & Jun Yang, 2020. "Weak convergence of iterative methods for solving quasimonotone variational inequalities," Computational Optimization and Applications, Springer, vol. 77(2), pages 491-508, November.
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    Cited by:

    1. Rizwan Anjum & Andreea Fulga & Muhammad Waqar Akram, 2023. "Applications to Solving Variational Inequality Problems via MR-Kannan Type Interpolative Contractions," Mathematics, MDPI, vol. 11(22), pages 1-11, November.
    2. Timilehin Opeyemi Alakoya & Oluwatosin Temitope Mewomo, 2023. "A Relaxed Inertial Tseng’s Extragradient Method for Solving Split Variational Inequalities with Multiple Output Sets," Mathematics, MDPI, vol. 11(2), pages 1-26, January.

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