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Characterization of Nonsmooth Quasiconvex Functions and their Greenberg–Pierskalla’s Subdifferentials Using Semi-Quasidifferentiability notion

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Abstract

The relationships between Greenberg–Pierskalla’s subdifferential and some variants of it and semi-quasidifferentials of quasiconvex functions are studied in this paper. Also, some characterizations of quasiconvex functions in terms of semi-quasidifferentials and the connection between quasimonotonicity of semi-quasidifferentials and quasiconvexity are investigated.

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References

  1. Abbasov, M.E.: Comparison between quasidifferentials and exhausters. J. Optim. Theory Appl. 175, 59–75 (2017). https://doi.org/10.1007/s10957-017-1167-3

    Article  MathSciNet  MATH  Google Scholar 

  2. Agrawal, A., Boyd, S.: Disciplined quasiconvex programming. Optim. Lett. 14, 1643–1657 (2020). https://doi.org/10.1007/s11590-020-01561-8

    Article  MathSciNet  MATH  Google Scholar 

  3. Antczak, T.: Optimality conditions in quasidifferentiable vector optimization. J. Optim. Theory Appl. 171, 708–725 (2016). https://doi.org/10.1007/s10957-016-0987-x

    Article  MathSciNet  MATH  Google Scholar 

  4. Aussel, D., Corvellec, J.N., Lassonde, M.: Subdifferential characterization of quasiconvexity and convexity. J. Convex Anal. 1, 195–201 (1994)

    MathSciNet  MATH  Google Scholar 

  5. Bagirov, A.: A method for minimization of quasidifferentiable functions. Optim. Method Softw. 17, 31–60 (2002). https://doi.org/10.1080/10556780290027837

    Article  MathSciNet  MATH  Google Scholar 

  6. Baier, R., Farkhi, E., Roshchina, V.: The directed and Rubinov subdifferentials of quasidifferentiable functions, Part I: definition and examples. Nonlin. Anal. Theory Methods Appl. 75, 1074–1088 (2012). https://doi.org/10.1016/j.na.2011.04.074

    Article  MathSciNet  MATH  Google Scholar 

  7. Baier, R., Farkhi, E., Roshchina, V.: From quasidifferentiable to directed subdifferentiable functions: exact calculus rules. J. Optim. Theory Appl. 171, 384–401 (2016). https://doi.org/10.1007/s10957-016-0926-x

    Article  MathSciNet  MATH  Google Scholar 

  8. Bui, H.T., Khanh, P.D., Tran, T.T.T.: Characterizations of nonsmooth robustly quasiconvex functions. J. Optim. Theory Appl. 180, 775–786 (2019). https://doi.org/10.1007/s10957-018-1421-3

    Article  MathSciNet  MATH  Google Scholar 

  9. Clarke, F.H., Ledyaev, Y.S., Stern, R.J., Wolenski, P.R.: Nonsmooth Analysis and Control theory. Springer-Verlag, New York (1998)

    MATH  Google Scholar 

  10. Daniilidis, A., Hadjisavvas, N.: Characterization of nonsmooth semistrictly quasiconvex and strictly quasiconvex functions. J. Optim. Theory Appl. 102, 525–536 (1999). https://doi.org/10.1023/A:1022693822102

    Article  MathSciNet  MATH  Google Scholar 

  11. Demyanov, V.F., Rubinov, A.M.: On quasidifferentiable functionals. Soviet Math Dokl 21, 14–17 (1980)

    MATH  Google Scholar 

  12. Dolgopolik, M.V.: Metric regularity of quasidifferentiable mappings and optimality conditions for nonsmooth mathematical programming problems. Set-Valued Var. Anal. 28, 427–449 (2020). https://doi.org/10.1007/s11228-019-00521-4

    Article  MathSciNet  MATH  Google Scholar 

  13. Dolgopolik, M.V.: A new constraint qualification and sharp optimality conditions for nonsmooth mathematical programming problems in terms of quasidifferentials. SIAM J. Optim. 30, 2603–2627 (2020). https://doi.org/10.1137/19M1293478

    Article  MathSciNet  MATH  Google Scholar 

  14. Dutta, J., Chandra, S.: Convexifactors, generalized convexity, and optimality conditions. J. Optim. Theory Appl. 113, 41–64 (2002). https://doi.org/10.1023/A:1014853129484

    Article  MathSciNet  MATH  Google Scholar 

  15. Ellaia, R., Hassouni, A.: Characterization of nonsmooth functions through their generalized gradients. Optimization 22, 401–416 (1991). https://doi.org/10.1080/02331939108843678

    Article  MathSciNet  MATH  Google Scholar 

  16. Ginchev, I., Martínez-Legaz, J.E.: Characterization of d.c. functions in terms of quasidifferentials. Nonlin. Anal. Theory Methods Appl. 74, 6781–6787 (2011). https://doi.org/10.1016/j.na.2011.07.003

    Article  MathSciNet  MATH  Google Scholar 

  17. Greenberg, H.J., Pierskalla, W.P.: Quasi-conjugate functions and surrogate duality. Cahiers du Centre détude de Recherche Operationelle 15, 437–448 (1973)

    MathSciNet  MATH  Google Scholar 

  18. Hassouni, A.: (1983) Sous-différentiels des fonctions quasi-convexes. Théese de \(3^e\) Cycle, Université Paul Sabatier

  19. Hishinuma, K., Iiduka, H.: Fixed point quasiconvex subgradient method. Eur. J. Oper. Res. 282, 428–437 (2020). https://doi.org/10.1016/j.ejor.2019.09.037

    Article  MathSciNet  MATH  Google Scholar 

  20. Jeyakumar, V., Luc, D.T.: Nonsmooth calculus, minimality, and monotonicity of convexificators. J. Optim. Theory Appl. 101, 599–621 (1999). https://doi.org/10.1023/A:1021790120780

    Article  MathSciNet  MATH  Google Scholar 

  21. Kabgani, A., Soleimani-damaneh, M.: Relationships between convexificators and Greenberg-Pierskalla subdifferentials for quasiconvex functions. Numer. Func. Anal. Optim. 38, 1548–1563 (2017). https://doi.org/10.1080/01630563.2017.1349144

    Article  MathSciNet  MATH  Google Scholar 

  22. Kanzi, N., Soleimani-damaneh, M.: Characterization of the weakly efficient solutions in nonsmooth quasiconvex multiobjective optimization. J. Glob. Optim. 77, 627–641 (2020). https://doi.org/10.1007/s10898-020-00893-0

    Article  MathSciNet  MATH  Google Scholar 

  23. Lin, S., Huang, M., Xia, Z., Li, D.: Quasidifferentiabilities of the expectation functions of random quasidifferentiable functions. Optimization (2020). https://doi.org/10.1080/02331934.2020.1818235

    Article  Google Scholar 

  24. Luc, D.T.: Characterizations of quasiconvex functions. Bull. Aust. Math. Soc. 48, 393–406 (1993). https://doi.org/10.1017/S0004972700015859

    Article  MATH  Google Scholar 

  25. Martínez-Legaz, J.E.: Generalized convex duality and its economic applicatons. In: Handbook of generalized convexity and generalized monotonicity, pp. 237–292. Springer, New York (2005)

  26. Mordukhovich, B.S.: Variational Analysis and Applications. Springer, Cham (2018)

    Book  Google Scholar 

  27. Penot, J.P.: Are generalized derivatives useful for generalized convex functions? In: Crouzeix, J.P., Martínez-Legaz, J.E., Volle, M. (eds.) Generalized convexity, generalized monotonicity: Recent results, pp. 3–59. Springer (1998)

  28. Plastria, F.: On the structure of the weakly efficient set for quasiconvex vector minimization. J. Optim. Theory Appl. 184, 547–564 (2020). https://doi.org/10.1007/s10957-019-01608-6

    Article  MathSciNet  MATH  Google Scholar 

  29. Pshenichnyi, B.N.: Necessary Conditions for an Extremum. Marcel Dekker Inc, New York (1971)

    Google Scholar 

  30. Soleimani-Damaneh, M.: Characterization of nonsmooth quasiconvex and pseudoconvex functions. J. Math. Anal. Appl. 330, 1387–1392 (2007). https://doi.org/10.1016/j.jmaa.2006.08.033

    Article  MathSciNet  MATH  Google Scholar 

  31. Sutti, C.: Quasidifferentiability of nonsmooth quasiconvex functions. Optimization 27, 313–319 (1993). https://doi.org/10.1080/02331939308843892

    Article  MathSciNet  MATH  Google Scholar 

  32. Suzuki, S.: Optimality conditions and constraint qualifications for quasiconvex programming. J. Optim. Theory Appl. 183, 963–976 (2019). https://doi.org/10.1007/s10957-019-01534-7

    Article  MathSciNet  MATH  Google Scholar 

  33. Suzuki, S.: Karush-Kuhn-Tucker type optimality condition for quasiconvex programming in terms of Greenberg-Pierskalla subdifferential. J. Glob. Optim. 79, 191–202 (2021). https://doi.org/10.1007/s10898-020-00926-8

    Article  MathSciNet  MATH  Google Scholar 

  34. Zhang, X., He, Z., Zhang, X., Peng, W.: High-performance beampattern synthesis via linear fractional semidefinite relaxation and quasi-convex optimization. IEEE Trans. Antennas Propag. 66, 3421–3431 (2018). https://doi.org/10.1109/TAP.2018.2835310

    Article  Google Scholar 

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Acknowledgements

The author would like to express his gratitude to the associate editor and anonymous referees for their helpful comments on the first version of this paper. The author also thanks Professor M. Soleimani-damaneh for useful discussions. This research was in part supported by a grant from IPM (No. 99900034).

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Correspondence to Alireza Kabgani.

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Communicated by Nicolas Hadjisavvas.

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Kabgani, A. Characterization of Nonsmooth Quasiconvex Functions and their Greenberg–Pierskalla’s Subdifferentials Using Semi-Quasidifferentiability notion. J Optim Theory Appl 189, 666–678 (2021). https://doi.org/10.1007/s10957-021-01851-w

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