Skip to main content

Advertisement

Log in

An approach to calmness of linear inequality systems from Farkas lemma

  • Original Paper
  • Published:
Optimization Letters Aims and scope Submit manuscript

Abstract

We deal with the feasible set mapping of linear inequality systems under right-hand side perturbations. From a version of Farkas lemma for difference of convex functions, we derive an operative relationship between calmness constants for this mapping at a nominal solution and associated neighborhoods where such constants work. We also provide illustrative examples where this approach allows us to compute the sharp Hoffman constant at the nominal system.

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.

Similar content being viewed by others

References

  1. Azé, D., Corvellec, J.-N.: Characterizations of error bounds for lower semicontinuous functions on metric spaces. ESAIM Control Optim. Calc. Var. 10, 409–425 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  2. Cánovas, M.J., Dontchev, A.L., López, M.A., Parra, J.: Metric regularity of semi-infinite constraint systems. Math. Program. Ser. B 104, 329–346 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  3. Cánovas, M.J., Hantoute, A., Parra, J., Toledo, F.J.: Calmness modulus of fully perturbed linear programs. Math. Program. Ser. A 158, 267–290 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  4. Cánovas, M.J., Henrion, R., López, M.A., Parra, J.: Outer limit of subdifferentials and calmness moduli in linear and nonlinear programming. J. Optim. Theory Appl. 169, 925–952 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  5. Cánovas, M.J., López, M.A., Parra, J., Toledo, F.J.: Calmness of the feasible set mapping for linear inequality systems. Set Valued Var. Anal. 22, 375–389 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  6. Cánovas, M.J., Parra, J., Rückmann, J.-J., Toledo, F.J.: Point-based neighborhoods for sharp calmness constants in linear programming. Set Valued Var. Anal. 25, 757–772 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  7. Dinh, N., Nghia, T.T.A., Vallet, G.: A closedness condition and its applications to DC programs with convex constraints. Optimization 59, 541–560 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  8. Dinh, N., Jeyakumar, V.: Farkas’ lemma: three decades of generalizations for mathematical optimization. Top 22, 1–22 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  9. Dontchev, A.L., Rockafellar, R.T.: Implicit Functions and Solution Mappings: A View from Variational Analysis. Springer, New York (2009)

    Book  MATH  Google Scholar 

  10. Goberna, M.A., López, M.A.: Linear Semi-Infinite Optimization. Wiley, Chichester (1998)

    MATH  Google Scholar 

  11. Henrion, R., Outrata, J.: Calmness of constraint systems with applications. Math. Program. Ser. B 104, 437–464 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  12. Hoffman, A.J.: On approximate solutions of systems of linear inequalities. J. Res. Nat. Bur. Stand. 49, 263–265 (1952)

    Article  MathSciNet  Google Scholar 

  13. Ioffe, A.D.: Necessary and sufficient conditions for a localminimum, part I: areduction theorem and first order conditions. SIAM J. Control Optim. 17, 245–250 (1979)

    Article  MathSciNet  Google Scholar 

  14. Ioffe, A.D.: Metric regularity and subdifferential calculus. Uspehi Mat. Nauk 55(3), 103–162 (2000). [(in Russian), English translation: Russian Math. Surv. 55(3) (2000), pp. 501–558]

    Article  MathSciNet  MATH  Google Scholar 

  15. Klatte, D., Kummer, B.: Nonsmooth Equations in Optimization: Regularity, Calculus, Methods and Applications. Nonconvex Optimization and Its Applications, vol. 60. Kluwer Academic, Dordrecht (2002)

    MATH  Google Scholar 

  16. Klatte, D., Kummer, B.: Optimization methods and stability of inclusions in Banach spaces. Math. Program. Ser. B 117, 305–330 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  17. Klatte, D., Thiere, G.: Error bounds for solutions of linear equations and inequalities. Math. Methods Oper. Res. 41, 191–214 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  18. Kruger, A., Van Ngai, H., Théra, M.: Stability of error bounds for convex constraint systems in Banach spaces. SIAM J. Optim. 20, 3280–3296 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  19. Li, W.: The sharp Lipschitz constants for feasible and optimal solutions of a perturbed linear program. Linear Algebra Appl. 187, 15–40 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  20. Li, W.: Sharp Lipschitz constants for basic optimal solutions and basic feasible solutions of linear programs. SIAM J. Control Optim. 32, 140–153 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  21. Meng, K.W., Yang, X.Q.: Equivalent conditions for local error bounds. Set Valued Var. Anal. 20, 617–636 (2012)

    Article  MathSciNet  MATH  Google Scholar 

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

    Google Scholar 

  23. Peña, J., Vera, J., Zuluaga, L.F.: An algorithm to compute the Hoffman constant of a system of linear constraints, preprint (2018). arXiv:1804.08418v1

  24. Robinson, S.M.: Some continuity properties of polyhedral multifunctions. In: Mathematical Programming at Oberwolfach (Proceedings of Conference Mathematisches Forschungsinstitut, Oberwolfach, 1979). Mathematical Programming Studies, vol. 14, pp. 206–214 (1981)

  25. Rockafellar, R.T.: Convex Analysis. Princeton University Press, Princeton (1970)

    Book  MATH  Google Scholar 

  26. Rockafellar, R.T., Wets, R.J.-B.: Variational Analysis. Springer, Berlin (1998)

    Book  MATH  Google Scholar 

  27. Zălinescu, C.: Convex Analysis in General Vector Spaces. World Scientific, Singapore (2002)

    Book  MATH  Google Scholar 

  28. Zălinescu, C.: Sharp estimates for Hoffman’s constant for systems of linear inequalities and equalities. SIAM J. Optim. 14, 517–533 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  29. Zheng, X.Y., Ng, K.F.: Metric regularity and constraint qualifications for convex inequalities on Banach spaces. SIAM J. Optim. 14, 757–772 (2003)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

The authors wish to thank the anonymous referees for their deep review of the original manuscript, which has definitely improved the quality of the paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to J. Parra.

Additional information

Publisher's Note

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

This research has been partially supported by Grant MTM2014-59179-C2-2-P from MINECO, Spain, and FEDER “Una manera de hacer Europa”, European Union, and by the Vietnam National University - Ho Chi Minh city, Vietnam, Project Gerneralized scalar and vector Farkas-type results with applications to optimization theory.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cánovas, M.J., Dinh, N., Long, D.H. et al. An approach to calmness of linear inequality systems from Farkas lemma. Optim Lett 13, 295–307 (2019). https://doi.org/10.1007/s11590-018-01380-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11590-018-01380-y

Keywords

Navigation