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Sequential characterizations of approximate solutions in convex vector optimization problems with set-valued maps

Author

Listed:
  • Nithirat Sisarat

    (Naresuan University)

  • Rabian Wangkeeree

    (Naresuan University
    Naresuan University)

  • Tamaki Tanaka

    (Niigata University)

Abstract

This paper deals with a convex vector optimization problem with set-valued maps. In the absence of constraint qualifications, it provides, by the scalarization theorem, sequential Lagrange multiplier conditions characterizing approximate weak Pareto optimal solutions for the problem in terms of the approximate subdifferentials of the marginal function associated with corresponding set-valued maps. The paper shows also that this result yields the approximate Lagrange multiplier condition for the problem under a new constraint qualification which is weaker than the Slater-type constraint qualification. Illustrative examples are also provided to discuss the significance of the sequential conditions.

Suggested Citation

  • Nithirat Sisarat & Rabian Wangkeeree & Tamaki Tanaka, 2020. "Sequential characterizations of approximate solutions in convex vector optimization problems with set-valued maps," Journal of Global Optimization, Springer, vol. 77(2), pages 273-287, June.
    • Handle: RePEc:spr:jglopt:v:77:y:2020:i:2:d:10.1007_s10898-019-00864-0
    DOI: 10.1007/s10898-019-00864-0
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    References listed on IDEAS

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    Cited by:

    1. Mohamed Laghdir & El Mahjoub. Echchaabaoui, 2023. "Sequential Pareto Subdifferential Sum Rule for Convex Set-Valued Mappings and Applications," Journal of Optimization Theory and Applications, Springer, vol. 198(3), pages 1226-1245, September.
    2. L. Q. Anh & T. Q. Duy & D. V. Hien, 2020. "Stability of efficient solutions to set optimization problems," Journal of Global Optimization, Springer, vol. 78(3), pages 563-580, November.

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