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Implicit function theorems for generalized equations

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Abstract

We show that Lipschitz and differentiability properties of a solution to a parameterized generalized equation 0 ∈f(x, y) + F(x), wheref is a function andF is a set-valued map acting in Banach spaces, are determined by the corresponding Lipschitz and differentiability properties of a solution toz ∈ g(x) + F(x), whereg strongly approximatesf in the sense of Robinson. In particular, the inverse map (f + F)−1 has a local selection which is Lipschitz continuous nearx 0 and Fréchet (Gateaux, Bouligand, directionally) differentiable atx 0 if and only if the linearization inverse (f (x 0) + f (x0) (× − x0) + F(×))−1 has the same properties. As an application, we study directional differentiability of a solution to a variational inequality.

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References

  1. A.L. Dontchev and W.W. Hager, “On Robinson's implicit function theorems,” in: A.B. Kurzhanski and V.M. Veliov, eds.,Set-valued Analysis and Differential Inclusions (Birkhäuser, Boston, MA, 1993) pp. 75–92.

    Google Scholar 

  2. A.L. Dontchev and W.W. Hager, “An inverse mapping theorem for set-valued maps,”Proceedings of the American Mathematical Society 121 (1994) 481–489.

    Google Scholar 

  3. A.L. Dontchev and W.W. Hager, “Implicit functions, Lipschitz maps, and stability in optimization,”Mathematics of Operations Research 19 (1994) 753–768.

    Google Scholar 

  4. A.L. Dontchev and T. Zolezzi,Well-Posed Optimization Problems, Lecture Notes in Mathematics, Vol. 1543 (Springer, Berlin, 1993).

    Google Scholar 

  5. A.J. King and R.T. Rockafellar, “Sensitivity analysis for nonsmooth generalized equations,”Mathematical Programming 55 (1992) 193–212.

    Google Scholar 

  6. J. Kyparisis, “Sensitivity analysis framework for variational inequalities,”Mathematical Programming 38 (1987) 203–213.

    Google Scholar 

  7. E.B. Leach, “A note on inverse function theorems,”Proceedings of the American Mathematical Society 12 (1961) 694–697.

    Google Scholar 

  8. A.B. Levy and R.T. Rockafellar, “Sensitivity analysis of solutions to generalized equations,”Transactions of the American Mathematical Society 345 (1994) 661–671.

    Google Scholar 

  9. K. Malanowski, “Two norm approach in stability and sensitivity analysis of optimization and optimal control problems,”Advances in Mathematical Sciences and Applications 2 (1993) 397–443.

    Google Scholar 

  10. A. Nijenhuis, “Strong derivatives and inverse mappings,”American Mathematical Monthly 81 (1974) 969–980.

    Google Scholar 

  11. J.S. Pang, “Newton's method for B-differentiable equations,”Mathematics of Operations Research 15 (1990) 311–341.

    Google Scholar 

  12. S.M. Robinson, “Strongly regular generalized equations,”Mathematics of Operations Research 5 (1980) 43–62.

    Google Scholar 

  13. S.M. Robinson, “Implicit B-differentiability in generalized equations”, Technical Summary Report No. 2854, Mathematics Research Center, University of Wisconsin-Madison, Madison, WI, 1985.

    Google Scholar 

  14. S.M. Robinson, “Local structure of feasible sets in nonlinear programming, Part III: Stability and sensitivity,”Mathematical Programming Study 30 (1987) 45–66.

    Google Scholar 

  15. S.M. Robinson, “An implicit-function theorem for a class of nonsmooth functions,”Mathematics of Operations Research 16 (1991) 292–309.

    Google Scholar 

  16. A. Shapiro, “On concepts of directional differentiability,”Journal of Optimization Theory and Applications 66 (1990) 477–487.

    Google Scholar 

  17. A. Shapiro, “Existence and differentiability of metric projections in Hilbert space,”SIAM Journal on Optimization 4 (1994) 130–141.

    Google Scholar 

  18. A. Shapiro, “Sensitivity analysis of parametrized programs via generalized equations,”SIAM Journal on Control and Optimization 32 (1994) 553–571.

    Google Scholar 

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This work was supported by National Science Foundation Grant Number DMS 9404431.

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Dontchev, A.L. Implicit function theorems for generalized equations. Mathematical Programming 70, 91–106 (1995). https://doi.org/10.1007/BF01585930

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  • DOI: https://doi.org/10.1007/BF01585930

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