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Local Linear Convergence of an Outer Approximation Projection Method for Variational Inequalities

Author

Listed:
  • Shu Lu

    (University of North Carolina at Chapel Hill)

  • Sudhanshu Singh

    (University of North Carolina at Chapel Hill)

Abstract

This paper considers an outer approximation projection method for variational inequalities, in which the projections are not performed on the original set that appears in the variational inequality, but on a polyhedral convex set defined by the linearized constraints. It shows that the method converges linearly, when the starting point is sufficiently close to the solution and the step lengths are sufficiently small.

Suggested Citation

  • Shu Lu & Sudhanshu Singh, 2011. "Local Linear Convergence of an Outer Approximation Projection Method for Variational Inequalities," Journal of Optimization Theory and Applications, Springer, vol. 151(1), pages 52-63, October.
    • Handle: RePEc:spr:joptap:v:151:y:2011:i:1:d:10.1007_s10957-011-9873-8
    DOI: 10.1007/s10957-011-9873-8
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    References listed on IDEAS

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    1. Stephen M. Robinson, 1991. "An Implicit-Function Theorem for a Class of Nonsmooth Functions," Mathematics of Operations Research, INFORMS, vol. 16(2), pages 292-309, May.
    2. Stephen M. Robinson, 1980. "Strongly Regular Generalized Equations," Mathematics of Operations Research, INFORMS, vol. 5(1), pages 43-62, February.
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