Skip to main content
Log in

On duality for mathematical programs with vanishing constraints

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

Abstract

In this paper, we formulate and study Wolfe and Mond–Weir type dual models for a difficult class of optimization problems known as the mathematical programs with vanishing constraints. We establish the weak, strong, converse, restricted converse and strict converse duality results under the assumptions of convexity and strict convexity between the primal mathematical program with vanishing constraints and the corresponding Wolfe type dual. We also derive the weak, strong, converse, restricted converse and strict converse duality results between the primal mathematical program with vanishing constraints and the corresponding Mond–Weir type dual under the assumptions of pseudoconvex, strict pseudoconvex and quasiconvex functions.

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.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Abadie, J. M. (1967). On the Kuhn–Tucker theorem. In J. M. Abadie (Ed.), Nonlinear programming (pp. 21–36). New York, NY: Wiley.

    Google Scholar 

  • Achtziger, W., & Kanzow, C. (2008). Mathematical programs with vanishing constraints: Optimality conditions and constraint qualifications. Mathematical Programming, 114, 69–99.

    Article  Google Scholar 

  • Antczak, T. (2010). G-saddle point criteria and G-Wolfe duality in differentiate mathematical programming. Journal of Information and Optimization Sciences, 31(1), 63–85.

    Article  Google Scholar 

  • Antczak, T., & Singh, V. (2013). Optimality and duality for minimax fractional programming with support functions under \(B\)-(\(p\), \(r\))- Type \(I\) assumptions. Mathematical and Computer Modelling, 57(5–6), 1083–1100.

    Article  Google Scholar 

  • Askar, S. S., & Tiwari, A. (2009). First-order optimality conditions and duality results for multi-objective optimization problems. Annals of Operations Research, 172(1), 277–289.

    Article  Google Scholar 

  • Bot̨, R. I., & Grad, S.-M. (2010). Wolfe duality and Mond–Weir duality via perturbations. Nonlinear Analysis: Theory, Methods and Applications, 73(2), 374–384.

    Article  Google Scholar 

  • Bot̨ R. I., & Heinrich, A. , (2014). Regression tasks in machine learning via Fenchel duality. Annals of Operations Research, 222, 197–211.

  • Bot̨, R. I., Grad, S.-M., & Wanka, G. (2009). Duality in vector optimization. In J. Jahn (Ed.), Vector optimization. Berlin/Heidelberg: Springer.

    Chapter  Google Scholar 

  • Cambini, A., & Martein, L. (2009). Generalized convexity and optimization: theory and applications. In G. Fandel & W. Trockel (Eds.), Lecture notes in economics and mathematical systems, Vol. 616. Berlin/Heidelberg: Springer.

  • Chinchuluun, A., Yuan, D., & Pardalos, P. M. (2007). Optimality conditions and duality for nondifferentiable multiobjective fractional programming with generalized convexity. Annals of Operations Research, 154(1), 133–147.

    Article  Google Scholar 

  • Gulati, T. R., & Mehndiratta, G. (2010). Nondifferentiable multiobjective Mond–Weir type second-order symmetric duality over cones. Optimization Letters, 4(2), 293–309.

    Article  Google Scholar 

  • Guo, L., Lin, G. H., & Ye, J. J. (2012). Stability analysis for parametric mathematical programs with geometric constraints and its applications. SIAM Journal on Optimization, 22(3), 1151–1176.

    Article  Google Scholar 

  • Hoheisel, T., & Kanzow, C. (2007). First and second order optimality conditions for mathematical programs with vanishing constraints. Applied Mathematics, 52(6), 495–514.

    Article  Google Scholar 

  • Hoheisel, T., & Kanzow, C. (2008). Stationary conditions for mathematical programs with vanishing constraints using weak constraint qualifications. Journal of Mathematical Analysis and Applications, 337, 292–310.

    Article  Google Scholar 

  • Hoheisel, T., & Kanzow, C. (2009). On the Abadie and Guignard constraint qualifications for mathematical programmes with vanishing constraints. Optimization, 58(4), 431–448.

    Article  Google Scholar 

  • Hoheisel, T., Kanzow, C., & Outrata, J. V. (2010). Exact penalty results for mathematical programs with vanishing constraints. Nonlinear Analysis, 72, 2154–2526.

    Article  Google Scholar 

  • Idrissi, H., Lefebvre, O., & Michelot, C. (1989). Duality for constrained multifacility location problems with mixed norms and applications. Annals of Operations Research, 18(1), 71–92.

    Article  Google Scholar 

  • Ito, S., Liu, Y., & Teo, K. L. (2000). A dual parametrization method for convex semi-infinite programming. Annals of Operations Research, 98(1–4), 189–213.

    Article  Google Scholar 

  • Izmailov, A. F., & Pogosyan, A. L. (2009). Optimality conditions and Newton-type methods for mathematical programs with vanishing constraints. Computational Mathematics and Mathematical Physics, 49, 1128–1140.

    Article  Google Scholar 

  • Izmailov, A. F., & Pogosyan, A. L. (2012). Active-set Newton methods for mathematical programs with vanishing constraints. Computational Optimization and Applications, 53, 425–452.doi:10.1007/s10589-012-9467-x.

  • Izmailov, A. F., & Solodov, M. V. (2009). Mathematical programs with vanishing constraints: Optimality conditions, sensitivity, and a relaxation method. Journal of Optimization Theory and Applications, 142, 501–532.

    Article  Google Scholar 

  • Jefferson, T. R., & Scott, C. H. (2001). Quality tolerancing and conjugate duality. Annals of Operations Research, 105(1–4), 185–200.

    Article  Google Scholar 

  • Jeyakumar, V., Lia, G., & Lee, G. M. (2012). Robust duality for generalized convex programming problems under data uncertainty. Nonlinear Analysis: Theory, Methods and Applications, 75(3), 1362–1373.

    Article  Google Scholar 

  • Lai, H.-C., & Huang, T.-Y. (2012). Nondifferentiable minimax fractional programming in complex spaces with parametric duality. Journal of Global Optimization, 53(2), 243–254.

    Article  Google Scholar 

  • Lee, J.-C., & Lai, H.-C. (2005). Parameter-free dual models for fractional programming with generalized invexity. Annals of Operations Research, 133(1–4), 47–61.

    Article  Google Scholar 

  • Mandal, P., & Nahak, C. (2011). Symmetric duality with \((p, r)-\rho -(\eta, \theta )-\)invexity. Applied Mathematics and Computation, 217, 8141–8148.

    Article  Google Scholar 

  • Mangasarian, O. L. (1994). Nonlineaer programming. McGraw-Hill, New York, 1969; reprinted as classics. Applied Mathematics 10, SIAM, Philadelphia.

  • Mishra, S. K., & Giorgi, G. (2008). Invexity and optimization. In Nonconvex optimization and its applications, Vol. 88. Berlin/Heidelberg: Springer

  • Mishra, S. K., & Shukla, K. (2010). Nonsmooth minimax programming problems with \(V\)-\(r\)-invex functions. Optimization, 59(1), 95–103.

    Article  Google Scholar 

  • Mishra, S. K., Jaiswal, M., & An, L. T. H. (2012). Duality for nonsmooth semi-infinite programming problems. Optimization Letters, 6, 261–271.

    Article  Google Scholar 

  • Mishra, S. K., Wang, S. Y., & Lai, K. K. (2008). V-invex functions and vector optimization. In P. M. Pardalos (Ed.), Optimization and its applications, Vol. 14. New York: Springer.

  • Mishra, S. K., Wang, S. Y., & Lai, K. K. (2009). Generalized convexity and vector optimization. In P. M. Pardalos (Ed.), Nonconvex optimization and its applications, Vol. 90. Berlin/Heidelberg: Springer

  • Mond, B., & Weir, T. (1981). Generalized concavity and duality. In S. Schaible & W. T. Ziemba (Eds.), Generalized concavity in optimization and economics (pp. 263–279). New York: Academic Press.

    Google Scholar 

  • Pini, R., & Singh, C. (1997). A survey of recent [1985–1995] advances in generalized convexity with applications to duality theory and optimality conditions. Optimization, 39(4), 311–360.

    Article  Google Scholar 

  • Peterson, D. W. (1973). A review of constraint qualifications in finite-dimensional spaces. SIAM Review, 15, 639–654.

    Article  Google Scholar 

  • Peterson, E. L. (2001). The fundamental relations between geometric programming duality, parametric programming duality, and ordinary Lagrangian duality. Annals of Operations Research, 105(1–4), 109–153.

    Article  Google Scholar 

  • Rockafellar, R. T. (1999). Duality and optimality in multistagestochastic programming. Annals of Operations Research, 85, 1–19.

    Article  Google Scholar 

  • Soleimani-damaneh, M. (2012). Duality for optimization problems in Banach algebras. Journal of Global Optimization, 54(2), 375–388.

    Article  Google Scholar 

  • Svaiter, B. F. (2011). A new duality theory for mathematical programming. Optimization, 60(8–9), 1209–1231.

    Article  Google Scholar 

  • Wolfe, P. (1961). A duality theorem for nonlinear programming. Quarterly of Applied Mathematics, 19, 239–244.

    Google Scholar 

Download references

Acknowledgments

The authors are thankful to the anonymous referees of the paper for their valuable comments and useful suggestions which helped to improve the paper in its present form and the editor. Author Vinay Singh is thankful to National Board for Higher Mathematics (NBHM), Department of Atomic Energy (DAE), Government of India for the Financial support as a Post Doctoral Fellow during the preparation of this manuscript. The research of Vivek Laha was supported by the Council of Scientific and Industrial Research (CSIR), New Delhi, Ministry of Human Resources Development, Government of India through University Grant Commission (UGC) Research Fellowship Grant 20-06/2010 (i) EU-IV. Currently, Vivek Laha is supported by NBHM Postdoctoral Fellowship of Department of Atomic Energy, Government of India (Ref. No. 2/40(47)/2014/R & D-II/1170).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Vivek Laha.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mishra, S.K., Singh, V. & Laha, V. On duality for mathematical programs with vanishing constraints. Ann Oper Res 243, 249–272 (2016). https://doi.org/10.1007/s10479-015-1814-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-015-1814-8

Keywords

Navigation