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Robust Necessary Optimality Conditions for Nondifferentiable Complex Fractional Programming with Uncertain Data

Author

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  • Jiawei Chen

    (Southwest University)

  • Suliman Al-Homidan

    (King Fahd University of Petroleum and Minerals)

  • Qamrul Hasan Ansari

    (King Fahd University of Petroleum and Minerals
    Aligarh Muslim University)

  • Jun Li

    (Southwest University)

  • Yibing Lv

    (Yangtze University)

Abstract

In this paper, we study robust necessary optimality conditions for a nondifferentiable complex fractional programming with uncertain data. A robust counterpart of uncertain complex fractional programming is introduced in the worst-case scenario. The concept of robust optimal solution of the uncertain complex fractional programming is introduced by using robust counterpart. We give an equivalence between the optimal solutions of the robust counterpart and a minimax nonfractional parametric programming. Finally, Fritz John-type and Karush–Kuhn–Tucker-type robust necessary optimality conditions of the uncertain complex fractional programming are established under some suitable conditions.

Suggested Citation

  • Jiawei Chen & Suliman Al-Homidan & Qamrul Hasan Ansari & Jun Li & Yibing Lv, 2021. "Robust Necessary Optimality Conditions for Nondifferentiable Complex Fractional Programming with Uncertain Data," Journal of Optimization Theory and Applications, Springer, vol. 189(1), pages 221-243, April.
    • Handle: RePEc:spr:joptap:v:189:y:2021:i:1:d:10.1007_s10957-021-01829-8
    DOI: 10.1007/s10957-021-01829-8
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    References listed on IDEAS

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    Cited by:

    1. Jie Wang & Shengjie Li & Min Feng, 2022. "Unified Robust Necessary Optimality Conditions for Nonconvex Nonsmooth Uncertain Multiobjective Optimization," Journal of Optimization Theory and Applications, Springer, vol. 195(1), pages 226-248, October.
    2. Wenyan Han & Guolin Yu, 2023. "Characterizations of multi-objective robustness solutions defined by Minkowski set difference," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(4), pages 1361-1380, December.

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