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On Classes of Generalized Convex Functions, Gordan–Farkas Type Theorems, and Lagrangian Duality

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  • J. B. G. Frenk

    (Erasmus University)

  • G. Kassay

    (Babes-Bolyai University)

Abstract

In this paper, we introduce several classes of generalized convex functions already discussed in the literature and show the relation between these classes. Moreover, a Gordan–Farkas type theorem is proved for all these classes and it is shown how these theorems can be used to verify strong Lagrangian duality results in finite-dimensional optimization.

Suggested Citation

  • J. B. G. Frenk & G. Kassay, 1999. "On Classes of Generalized Convex Functions, Gordan–Farkas Type Theorems, and Lagrangian Duality," Journal of Optimization Theory and Applications, Springer, vol. 102(2), pages 315-343, August.
    • Handle: RePEc:spr:joptap:v:102:y:1999:i:2:d:10.1023_a:1021780423989
    DOI: 10.1023/A:1021780423989
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    References listed on IDEAS

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    1. Illés, T. & Kassay, G., 1994. "Farkas type theorems for generalized convexities," Pure Mathematics and Applications, Department of Mathematics, Corvinus University of Budapest, vol. 5(2), pages 225-239.
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    Cited by:

    1. Maria C. Maciel & Sandra A. Santos & Graciela N. Sottosanto, 2016. "On the Fritz John saddle point problem for differentiable multiobjective optimization," OPSEARCH, Springer;Operational Research Society of India, vol. 53(4), pages 917-933, December.
    2. Frenk, J.B.G. & Kassay, G., 2004. "Introduction to Convex and Quasiconvex Analysis," ERIM Report Series Research in Management ERS-2004-075-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Fabián Flores-Bazán & Fernando Flores-Bazán & Cristián Vera, 2012. "A complete characterization of strong duality in nonconvex optimization with a single constraint," Journal of Global Optimization, Springer, vol. 53(2), pages 185-201, June.
    4. Radu Boţ & Sorin-Mihai Grad & Gert Wanka, 2007. "A general approach for studying duality in multiobjective optimization," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 65(3), pages 417-444, June.
    5. Adan, M. & Novo, V., 2003. "Weak efficiency in vector optimization using a closure of algebraic type under cone-convexlikeness," European Journal of Operational Research, Elsevier, vol. 149(3), pages 641-653, September.
    6. Fabián Flores-Bazán & William Echegaray & Fernando Flores-Bazán & Eladio Ocaña, 2017. "Primal or dual strong-duality in nonconvex optimization and a class of quasiconvex problems having zero duality gap," Journal of Global Optimization, Springer, vol. 69(4), pages 823-845, December.
    7. Frenk, J.B.G. & Kassay, G., 2005. "Lagrangian duality and cone convexlike functions," ERIM Report Series Research in Management ERS-2005-019-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    8. C. Gutiérrez & B. Jiménez & V. Novo, 2006. "On Approximate Efficiency in Multiobjective Programming," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 64(1), pages 165-185, August.
    9. J. B. G. Frenk & G. Kassay, 2007. "Lagrangian Duality and Cone Convexlike Functions," Journal of Optimization Theory and Applications, Springer, vol. 134(2), pages 207-222, August.
    10. M. Adán & V. Novo, 2004. "Proper Efficiency in Vector Optimization on Real Linear Spaces," Journal of Optimization Theory and Applications, Springer, vol. 121(3), pages 515-540, June.
    11. Giorgio Giorgi, 2014. "Again on the Farkas Theorem and the Tucker Key Theorem Proved Easily," DEM Working Papers Series 094, University of Pavia, Department of Economics and Management.
    12. Jiawei Chen & Elisabeth Köbis & Jen-Chih Yao, 2019. "Optimality Conditions and Duality for Robust Nonsmooth Multiobjective Optimization Problems with Constraints," Journal of Optimization Theory and Applications, Springer, vol. 181(2), pages 411-436, May.
    13. J. B. G. Frenk & P. Kas & G. Kassay, 2007. "On Linear Programming Duality and Necessary and Sufficient Conditions in Minimax Theory," Journal of Optimization Theory and Applications, Springer, vol. 132(3), pages 423-439, March.
    14. Frenk, J.B.G. & Still, G.J., 2005. "A Note on the Dual of an Unconstrained (Generalized) Geometric Programming Problem," ERIM Report Series Research in Management ERS-2005-006-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    15. Gutiérrez, C. & Jiménez, B. & Novo, V., 2012. "Improvement sets and vector optimization," European Journal of Operational Research, Elsevier, vol. 223(2), pages 304-311.
    16. R. I. Boţ & S. M. Grad & G. Wanka, 2007. "New Constraint Qualification and Conjugate Duality for Composed Convex Optimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 135(2), pages 241-255, November.

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