Skip to main content
Log in

On higher-order proto-differentiability of perturbation maps

  • Published:
Positivity Aims and scope Submit manuscript

Abstract

This paper is concerned with higher-order sensitivity analysis in parametric vector optimization problems. Firstly, higher-order proto-differentiability of a set-valued mapping from one Euclidean space to another is defined. Then, we prove that the perturbation map/the proper perturbation map/the weak perturbation map of a parameterized vector optimization problem are higher-order proto-differentiable under some suitable qualification conditions.

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.

Institutional subscriptions

We’re sorry, something doesn't seem to be working properly.

Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

References

  1. Anh, N.L.H., Khanh, P.Q., Tung, L.T.: Higher-order radial derivatives and optimality conditions in nonsmooth vector optimization. Nonlinear Anal. 74, 7365–7379 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  2. Anh, N.L.H., Khanh, P.Q.: Variational sets of pertubation maps and applications to sensitivity analysis for constrained vector optimization. J. Optim. Theory Appl. 158, 363–384 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  3. Anh, N.L.H.: Some results on sensitivity analysis in set-valued optimization. Positivity 21, 1527–1543 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  4. Anh, N.L.H.: Sensitivity analysis in constrained set-valued optimization via Studniarski derivatives. Positivity 21, 255–272 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  5. Anh, N.L.H.: On sensitivity analysis of parametric set-valued equilibrium problems under the weak efficiency. Positivity 23, 139–159 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  6. Aubin, J.P., Frankowska, H.: Set-Valued Analysis. Birkhäuser, Boston (1990)

    MATH  Google Scholar 

  7. Balbás, A., Jiménez Guerra, P.: Sensitivity analysis for convex multiobjective programming in abstract spaces. J. Math. Anal. Appl. 202, 645–648 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  8. Chuong, T.D., Yao, J.-C.: Generalized Clarke epiderivatives of parametric vector optimization problems. J. Optim. Theory Appl. 146, 77–94 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  9. Chuong, T.D.: Clarke coderivatives of efficient point multifunctions in parametric vector optimization. Nonlinear Anal. 74, 273–285 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  10. Chuong, T.D.: Derivatives of the efficient point multifunction in parametric vector optimization problems. J. Optim. Theory Appl. 156, 247–265 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  11. Chuong, T.D.: Normal subdifferentials of effcient point multifunctions in parametric vector optimization. Optim. Lett. 7, 1087–1117 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  12. Chuong, T.D., Yao, J.C.: Fréchet subdifferentials of efficient point multifunctions in parametric vector optimization. J. Global Optim. 57, 1229–1243 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  13. Diem, H.T.H., Khanh, P.Q., Tung, L.T.: On higher-order sensitivity analysis in nonsmooth vector optimization. J. Optim. Theory Appl. 162, 463–488 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  14. Frankowska, H.: An open mapping principle for set-valued maps. J. Math. Anal. Appl. 127, 172–180 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  15. Frankowska, H., Quincampoix, M.: Hölder metric regularity of set-valued maps. Math. Program. 132, 333–345 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  16. García, F., Melguizo Padial, M.A.: Sensitivity analysis in convex optimization through the circatangent derivative. J. Optim. Theory Appl. 165, 420–438 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  17. Huy, N.Q., Lee, G.M.: Sensitivity of solutions to a parametric generalized equation. Set-Valued Anal. 16, 805–820 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  18. Jiménez Guerra, P., Melguizo, M.A., Muñoz, M.J.: Sensitivity analysis in convex programming. Comput. Math. Appl. 58, 1239–1246 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  19. Jiménez Guerra, P., Melguizo Padial, M.A.: Sensitivity analysis in differential programming through the Clarke derivative. Mediterr. J. Math. 9, 537–550 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  20. Kuk, H., Tanino, T., Tanaka, M.: Sensitivity analysis in vector optimization. J. Optim. Theory Appl. 89, 713–730 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  21. Lee, G.M., Huy, N.Q.: On proto-differentiablility of generalized perturbation maps. J. Math. Anal. Appl. 324, 1297–1309 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  22. Lee, G.M., Huy, N.Q.: On sensitivity analysis in vector optimization. Taiwanese J. Math. 11, 945–958 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  23. Levy, A.B., Rockafellar, R.T.: Sensitivity analysis of solutions to generalized equations. Trans. Am. Math. Soc. 345, 661–671 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  24. Li, S.J., Liao, C.M.: Second-order differentiability of generalized perturbation maps. J. Global Optim. 52, 243–252 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  25. Mordukhovich, B.S.: Variational Analysis and Generalized Differentiation, Vol. I: Basic Theory. Springer, Berlin (2006)

  26. Mordukhovich, B.S.: Variational Analysis and Generalized Differentiation, Vol. Applications. Springer, Berlin, II (2006)

  27. Mordukhovich, B.S.: Variational Analysis and Applications. Springer, New York (2018)

    Book  MATH  Google Scholar 

  28. Mordukhovich, B.S., Rockafellar, R.T.: Second-order subdifferential calculus with applications to tilt stability in optimization. SIAM J. Optim. 22, 953–986 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  29. Mordukhovich, B.: Equilibrium problems with equilibrium constraints via multiobjective optimization. Optim. Methods Softw. 19, 479–492 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  30. Mordukhovich, B.S., Nam, N.M., Yen, N.D.: Subgradients of marginal functions in parametric mathematical programming. Math. Progr. 116, 369–396 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  31. Mordukhovich, B.S., Nam, N.M.: Variational analysis of extended generalized equations via coderivative calculus in Asplund spaces. J. Math. Anal. Appl. 350, 663–679 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  32. Rockafellar, R.T.: Proto-differentiablility of set-valued mappings and its applications in optimization. Ann. Inst. H. Poincaré Anal. Non Linéaire 6, 449–482 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  33. Shi, D.S.: Contingent derivative of the perturbation map in multiobjective optimization. J. Optim. Theory Appl 70, 385–396 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  34. Shi, D.S.: Sensitivity analysis in convex vector optimization. J. Optim. Theory Appl. 77, 145–159 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  35. Studniarski, M.: Necessary and sufficient conditions for isolated local minima of nonsmooth functions. SIAM J. Control Optim. 24, 1044–1049 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  36. Studniarski, M., Ward, D.: Weak sharp minima: characterizations and sufficient condition. SIAM J. Control Optim. 38, 219–236 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  37. Sun, X.K., Li, S.J.: Stability analysis for higher-order adjacent derivative in parametrized vector optimization. J. Inequal. Appl. 2010, Article ID 510838 (2010)

  38. Sun, X.K., Li, S.J.: Lower Studniarski derivative of the perturbation map in parameterized vector optimization. Optim. Lett. 5, 601–614 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  39. Tanino, T.: Sensitivity analysis in multiobjective optimization. J. Optim. Theory Appl. 56, 479–499 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  40. Tanino, T.: Stability and sensitivity analysis in convex vector optimization. SIAM J. Control Optim. 26, 521–536 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  41. Tung, L.T.: On higher-order adjacent derivative of perturbation map in parametric vector optimization. J. Inequal. Appl. 2016, Article ID 112 (2016)

  42. Tung, L.T.: Variational sets and asymptotic variational sets of proper perturbation map in parametric vector optimization. Positivity 21, 1647–1673 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  43. Tung, L.T.: Second-order radial-asymptotic derivatives and applications in set-valued vector optimization. Pacific J. Optim. 13, 137–153 (2017)

    MathSciNet  Google Scholar 

  44. Tung, L.T.: On second-order proto-differentiability of perturbation maps. Set-Valued Var. Anal. 26, 561–579 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  45. Wang, Q.L., Li, S.J.: Sensitivity and stability for the second-order contingent derivative of the proper perturbation map in vector optimization. Optim. Lett. 6, 731–748 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  46. Wang, Q.L., Li, S.J.: Second-order contingent derivative of the pertubation map in multiobjective optimization. Fixed Point Theory Appl. 2011, Article ID 857520 (2011)

Download references

Acknowledgements

The author would like to thank the Editors for the help in the processing of the article. The author is very grateful to the Associate Editor and the Anonymous Referee for the valuable remarks, which helped to improve the paper. This work is partially supported by Can Tho University.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to L. T. Tung.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tung, L.T. On higher-order proto-differentiability of perturbation maps. Positivity 24, 441–462 (2020). https://doi.org/10.1007/s11117-019-00689-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11117-019-00689-x

Keywords

Mathematics Subject Classification

Navigation