Skip to main content
Log in

On optimality conditions and duality theorems for robust semi-infinite multiobjective optimization problems

  • RAOTA-2016
  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

In this paper, we consider a semi-infinite multiobjective optimization problem with more than two differentiable objective functions and uncertain constraint functions, which is called a robust semi-infinite multiobjective optimization problem and give its robust counterpart \({\mathrm{(RSIMP)}}\) of the problem, which is regarded as the worst case of the uncertain semi-infinite multiobjective optimization problem. We prove a necessary optimality theorem for a weakly robust efficient solution of \({\mathrm{(RSIMP)}} \), and then give a sufficient optimality theorem for a weakly robust efficient solution of \({\mathrm{(RSIMP)}}\). We formulate a Wolfe type dual problem of \({\mathrm{(RSIMP)}}\) and give duality results which hold between \({\mathrm{(RSIMP)}}\) and its dual problem.

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

Similar content being viewed by others

References

  • Aubin, J.-P. (1979). Mathematical Methods of Game and Economic Theory. Amsterdam: North-Holland Publishing Company.

    Google Scholar 

  • Beck, A., & Ben-Tal, A. (2009). Duality in robust optimization: Primal worst equals dual best. Operations Research Letters, 37, 1–6.

    Article  Google Scholar 

  • Ben-Tal, A., Ghaoui, L. E., & Nemirovski, A. (2009). Robust optimzation. Princeton series in applied mathematics. Priceton, NJ: Priceton University Press.

    Google Scholar 

  • Ben-Tal, A., & Nemirovski, A. (1999). Robust solutions to uncertain linear programs. Operations Research Letters, 25, 1–13.

    Article  Google Scholar 

  • Ben-Tal, A., & Nemirovski, A. (2002). Robust optimization-methodology and applications. Mathematical programming, series B, 92, 453–480.

    Article  Google Scholar 

  • Ben-Tal, A., & Nemirovski, A. (2008). A selected topics in robust convex optimization. Mathematical programming, series B, 112, 125–158.

    Article  Google Scholar 

  • Bonnans, J. F., & Shapiro, A. (2000). Perturbation Analysis of Optimization Problems. New York: Springer.

    Book  Google Scholar 

  • Chuong, T. D. (2016). Optimality and duality for robust multiobjective optimization Problems. Nonlinear Analysis, 134, 127–143.

    Article  Google Scholar 

  • Chuong, T. D., & Kim, D. S. (2014). Nonsmooth semi-infinite multiobjective optimization problems. Journal of Optimization Theory and Applications, 160, 748–762.

    Article  Google Scholar 

  • Goberna, M. A., Guerra-Vazquez, F., & Todorov, M. I. (2013). Constraint qualifications in linear vector semi-infinite optimization. European Journal of Operational Research, 227, 12–21.

    Article  Google Scholar 

  • Goberna, M. A., Jeyakumar, V., Li, G., & Lopez, M. A. (2013). Robust linear semi-infinite programming duality under uncertainty. Mathematical programming, series B, 139, 185–203.

    Article  Google Scholar 

  • Goberna, M. A., Jeyakumar, V., Li, G., & Vicente-Perez, J. (2014). Robust solutions of multi-objective linear semi-infinite programs under constraint data uncertainty. SIAM Journal on Optimization, 24, 1402–1419.

    Article  Google Scholar 

  • Goberna, M. A., & Lopez, M. A. (1998). Linear semi-infinite optimization. Chichester: Wiley.

    Google Scholar 

  • Jeyakumar, V., Lee, G. M., & Li, G. (2015). Characterizing robust solutions sets convex programs under data uncertainty. Journal of Optimization Theory and Applications, 64, 407–435.

    Article  Google Scholar 

  • Jeyakumar, V., & Li, G. (2010). Characterizing robust set containments and solutions of uncertain linear programs without qualifications. Operations Research Letters, 38, 188–194.

    Article  Google Scholar 

  • Jeyakumar, V., & Li, G. (2010). Strong duality in robust convex programming: Complete characterizations. SIAM Journal on Optimization, 20, 3384–3407.

    Article  Google Scholar 

  • Jeyakumar, V., & Li, G. (2014). Robust semi-definite linear programming duality under data uncertainty. Optimization, 63, 713–733.

    Article  Google Scholar 

  • Jeyakumar, V., Li, G., & Lee, G. M. (2012). Robust duality for generalized convex programming problems under data uncertainty. Nonlinear Analysis, 75, 1362–1373.

    Article  Google Scholar 

  • Kuroiwa, D., & Lee, G. M. (2012). On robust multiobjective optimization. Vietnam Journal of Mathematics, 40, 305–317.

    Google Scholar 

  • Kuroiwa, D., & Lee, G. M. (2014). On robust convex multiobjective optimization. Journal of Nonlinear and Convex Analysis, 15, 1125–1136.

    Google Scholar 

  • Lee, J. H., & Jiao, L. (2016). On quasi \(\epsilon \)-solution for robust convex optimization problems. Optimization Letters. doi:10.1007/s11590-016-1067-8.

  • Lee, J. H., & Lee, G. M. (2012). On \(\epsilon \)-solutions for convex optimization problems with uncertainty data. Positivity, 16, 509–526.

    Article  Google Scholar 

  • Lee, G. M., & Lee, J. H. (2015). On nonsmooth optimality theorems for robust multiobjective optimization problems. Journal of Nonlinear and Convex Analysis, 16, 2039–2052.

    Google Scholar 

  • Lee, J. H., & Lee, G. M. (2015). On sequential optimality conditions for robust multiobjective convex optimization problems. Linear and Nonlinear Analysis, 1, 221–246.

    Google Scholar 

  • Li, G. Y., Jeyakumar, V., & Lee, G. M. (2011). Robust conjugate duality for convex optimization under uncertainty with application to data classification. Nonlinear Analysis, 74, 2327–2341.

    Article  Google Scholar 

  • Suzuki, S., Kuroiwa, D., & Lee, G. M. (2013). Surrogate duality for robust optimization. European Journal of Operational Research, 231, 257–262.

    Article  Google Scholar 

Download references

Acknowledgments

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

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gue Myung Lee.

Additional information

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2013R1A1A2005378).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, J.H., Lee, G.M. On optimality conditions and duality theorems for robust semi-infinite multiobjective optimization problems. Ann Oper Res 269, 419–438 (2018). https://doi.org/10.1007/s10479-016-2363-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-016-2363-5

Keywords

Mathematics Subject Classification

Navigation