Skip to main content
Log in

Quasi \(\epsilon \)-solutions in a semi-infinite programming problem with locally Lipschitz data

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

Abstract

Under the fulfilment of the limiting constraint qualification, a necessary condition for a quasi \(\epsilon \)-solution to a semi-infinite programming problem (SIP) by means of employing some advanced tools of variational analysis and generalized differential is established. Sufficient conditions for such a quasi \(\epsilon \)-solution to problem (SIP) are also investigated in light of generalized convex functions defined in terms of the limiting subdifferential of locally Lipschitz functions. Finally, a Wolfe type dual model in approximate form is formulated, and weak, strong and converse-like duality theorems are proposed. Besides, we give some simple examples to illustrate the obtained results.

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. Burachik, R.S., Yang, X.Q., Zhou, Y.Y.: Existence of augmented Lagrange multipliers for semi-infinite programming problems. J. Optim. Theory Appl. 173, 471–503 (2017)

    Article  MathSciNet  Google Scholar 

  2. Chuong, T.D.: Nondifferentiable fractional semi-infinite multiobjective optimization problems. Oper. Res. Lett. 44, 260–266 (2016)

    Article  MathSciNet  Google Scholar 

  3. Chuong, T.D., Huy, N.Q., Yao, J.C.: Subdifferentials of marginal functions in semi-infinite programming. SIAM J. Optim. 20, 1462–1477 (2009)

    Article  MathSciNet  Google Scholar 

  4. Chuong, T.D., Kim, D.S.: Nonsmooth semi-infinite multiobjective optimization problems. J. Optim. Theory Appl. 160, 748–762 (2014)

    Article  MathSciNet  Google Scholar 

  5. Chuong, T.D., Kim, D.S.: Approximate solutions of multiobjective optimization problems. Positivity 20, 187–207 (2016)

    Article  MathSciNet  Google Scholar 

  6. Chuong, T.D., Yao, J.C.: Isolated and proper efficiencies in semi-infinite vector optimization problems. J. Optim. Theory Appl. 162, 447–462 (2014)

    Article  MathSciNet  Google Scholar 

  7. Dinh, D., Goberna, M.A., López, M.A., Son, T.Q.: New Farkas-type constraint qualifications in convex infinite programming. ESAIM Control Optim. Calc. Var. 13, 580–597 (2007)

    Article  MathSciNet  Google Scholar 

  8. Dutta, J., Deb, K., Tulshyan, R., Arora, R.: Approximate KKT points and a proximity measure for termination. J. Glob. Optim. 56, 1463–1499 (2013)

    Article  MathSciNet  Google Scholar 

  9. Ekeland, I.: On the variational principle. J. Math. Anal. Appl. 47, 324–353 (1974)

    Article  MathSciNet  Google Scholar 

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

    MATH  Google Scholar 

  11. Goberna, M.A., López, M.A.: Recent contributions to linear semi-infinite optimization. 4OR 15, 221–264 (2017)

    Article  MathSciNet  Google Scholar 

  12. Goberna, M.A., López, M.A.: Recent contributions to linear semi-infinite optimization: an update. Ann. Oper. Res. 271, 237–278 (2018)

    Article  MathSciNet  Google Scholar 

  13. Hong, Z., Bae, K.D., Kim, D.S.: Optimality conditions in convex optimization with locally Lipschitz constraints. Optim. Lett. 13, 1059–1068 (2019)

    Article  MathSciNet  Google Scholar 

  14. Jiao, L.G., Lee, J.H.: Approximate optimality and approximate duality for quasi approximate solutions in robust convex semidefinite programs. J. Optim. Theory Appl. 176(2), 74–93 (2018)

    Article  MathSciNet  Google Scholar 

  15. Kim, D.S., Son, T.Q.: Characterizations of solution sets of a class of nonconvex semi-infinite programming problems. J. Nonlinear Convex Anal. 12, 429–440 (2011)

    MathSciNet  MATH  Google Scholar 

  16. Kim, D.S., Son, T.Q.: An approach to \(\epsilon \)-duality theorems for nonconvex semi-infinite multiobjective optimization problems. Taiwan. J. Math. 22, 1261–1287 (2018)

    MathSciNet  MATH  Google Scholar 

  17. Lee, J.H., Jiao, L.G.: On quasi \(\epsilon \)-solution for robust convex optimization problems. Optim. Lett. 11(8), 1609–1622 (2017)

    Article  MathSciNet  Google Scholar 

  18. Li, C., Ng, K.F., Pong, T.K.: Constraint qualifications for convex inequality systems with applications in constrained optimization. SIAM J. Optim. 19, 163–187 (2008)

    Article  MathSciNet  Google Scholar 

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

    Book  Google Scholar 

  20. Mordukhovich, B.S.: Variational Analysis and Applications. Springer Monographs in Mathematics, p. XIX+622. Springer, Cham (2018)

    Book  Google Scholar 

  21. Mordukhovich, B.S., Nghia, T.T.A.: Subdifferentials of nonconvex supremum functions and their applications to semi-infinite and infinite programs with Lipschitzian data. SIAM J. Optim. 23(1), 406–431 (2013)

    Article  MathSciNet  Google Scholar 

  22. Mordukhovich, B.S., Nghia, T.T.A.: Nonsmooth cone-constrained optimization with applications to semi-infinite programming. Math. Oper. Res. 39(2), 301–324 (2014)

    Article  MathSciNet  Google Scholar 

  23. Piao, G.-R., Jiao, L.G., Kim, D.S.: Optimality conditions in nonconvex semi-infinite multiobjective optimization problems. J. Nonlinear Convex Anal. 17, 167–175 (2016)

    MathSciNet  MATH  Google Scholar 

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

    Book  Google Scholar 

  25. Son, T.Q., Kim, D.S.: A new approach to characterize the solution set of a pseudoconvex programming problem. J. Comput. Appl. Math. 261, 333–340 (2014)

    Article  MathSciNet  Google Scholar 

  26. Son, T.Q., Strodiot, J.J., Nguyen, V.H.: \(\epsilon \)-Optimality and \(\epsilon \)-Lagrangian duality for a nonconvex programming problem with an infinite number of constraints. J. Optim. Theory Appl. 141, 389–409 (2009)

    Article  MathSciNet  Google Scholar 

  27. Son, T.Q., Tuyen, N.V., Wen, C.-F.: Optimality conditions for approximate Pareto solutions of a nonsmooth vector optimization problem with an infinite number of constraints. arXiv:1808.10100 (2018)

Download references

Acknowledgements

The authors would like to express their sincere thanks to anonymous referees for the valuable suggestions and comments for the paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Do Sang Kim.

Additional information

Publisher's Note

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

Liguo Jiao was partially supported by National Center for Theoretical Sciences (NCTS) of Taiwan. Do Sang Kim was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korean Government (NRF-2019R1A2C1008672). Yuying Zhou was supported by the National Natural Sciences Foundation of China (11771319).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jiao, L., Kim, D.S. & Zhou, Y. Quasi \(\epsilon \)-solutions in a semi-infinite programming problem with locally Lipschitz data. Optim Lett 15, 1759–1772 (2021). https://doi.org/10.1007/s11590-019-01457-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11590-019-01457-2

Keywords

Mathematics Subject Classification

Navigation