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Predictor–Corrector Methods for General Regularized Nonconvex Variational Inequalities

Author

Listed:
  • Qamrul Hasan Ansari

    (Aligarh Muslim University
    King Fahd University of Petroleum & Minerals)

  • Javad Balooee

    (Islamic Azad University)

Abstract

This paper is devoted to the study of a new class of nonconvex variational inequalities, named general regularized nonconvex variational inequalities. By using the auxiliary principle technique, a new modified predictor–corrector iterative algorithm for solving general regularized nonconvex variational inequalities is suggested and analyzed. The convergence of the iterative algorithm is established under the partially relaxed monotonicity assumption. As a consequence, the algorithm and results presented in the paper overcome incorrect algorithms and results existing in the literature.

Suggested Citation

  • Qamrul Hasan Ansari & Javad Balooee, 2013. "Predictor–Corrector Methods for General Regularized Nonconvex Variational Inequalities," Journal of Optimization Theory and Applications, Springer, vol. 159(2), pages 473-488, November.
    • Handle: RePEc:spr:joptap:v:159:y:2013:i:2:d:10.1007_s10957-013-0352-2
    DOI: 10.1007/s10957-013-0352-2
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    Cited by:

    1. Javad Balooee, 2017. "Regularized Nonconvex Mixed Variational Inequalities: Auxiliary Principle Technique and Iterative Methods," Journal of Optimization Theory and Applications, Springer, vol. 172(3), pages 774-801, March.
    2. Javad Balooee & Shih-Sen Chang & Lin Wang & Zhaoli Ma, 2022. "Algorithmic Aspect and Convergence Analysis for System of Generalized Multivalued Variational-like Inequalities," Mathematics, MDPI, vol. 10(12), pages 1-40, June.

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