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Constraint Qualifications and Stationary Conditions for Mathematical Programming with Non-differentiable Vanishing Constraints

Author

Listed:
  • Sajjad Kazemi

    (Payam Noor University)

  • Nader Kanzi

    (Payam Noor University)

Abstract

This paper aims at studying a broad class of mathematical programming with non-differentiable vanishing constraints. First, we are interested in some various qualification conditions for the problem. Then, these constraint qualifications are applied to obtain, under different conditions, several stationary conditions of type Karush/Kuhn–Tucker.

Suggested Citation

  • Sajjad Kazemi & Nader Kanzi, 2018. "Constraint Qualifications and Stationary Conditions for Mathematical Programming with Non-differentiable Vanishing Constraints," Journal of Optimization Theory and Applications, Springer, vol. 179(3), pages 800-819, December.
  • Handle: RePEc:spr:joptap:v:179:y:2018:i:3:d:10.1007_s10957-018-1373-7
    DOI: 10.1007/s10957-018-1373-7
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    References listed on IDEAS

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    1. J. V. Burke & A. S. Lewis & M. L. Overton, 2002. "Approximating Subdifferentials by Random Sampling of Gradients," Mathematics of Operations Research, INFORMS, vol. 27(3), pages 567-584, August.
    2. Nguyen Huy Chieu & Gue Myung Lee, 2014. "Constraint Qualifications for Mathematical Programs with Equilibrium Constraints and their Local Preservation Property," Journal of Optimization Theory and Applications, Springer, vol. 163(3), pages 755-776, December.
    3. HALKIN, Hubert, 1974. "Implicit functions and optimization problems without continuous differentiability of the data," LIDAM Reprints CORE 184, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Do Luu, 2016. "Optimality Condition for Local Efficient Solutions of Vector Equilibrium Problems via Convexificators and Applications," Journal of Optimization Theory and Applications, Springer, vol. 171(2), pages 643-665, November.
    5. Giancarlo Bigi & Massimo Pappalardo & Mauro Passacantando, 2016. "Optimization Tools for Solving Equilibrium Problems with Nonsmooth Data," Journal of Optimization Theory and Applications, Springer, vol. 171(3), pages 887-905, December.
    6. Wolfgang Achtziger & Tim Hoheisel & Christian Kanzow, 2013. "A smoothing-regularization approach to mathematical programs with vanishing constraints," Computational Optimization and Applications, Springer, vol. 55(3), pages 733-767, July.
    7. S. K. Mishra & Vinay Singh & Vivek Laha, 2016. "On duality for mathematical programs with vanishing constraints," Annals of Operations Research, Springer, vol. 243(1), pages 249-272, August.
    8. A. F. Izmailov & M. V. Solodov, 2009. "Mathematical Programs with Vanishing Constraints: Optimality Conditions, Sensitivity, and a Relaxation Method," Journal of Optimization Theory and Applications, Springer, vol. 142(3), pages 501-532, September.
    9. Nooshin Movahedian, 2017. "Bounded Lagrange multiplier rules for general nonsmooth problems and application to mathematical programs with equilibrium constraints," Journal of Global Optimization, Springer, vol. 67(4), pages 829-850, April.
    10. Yogendra Pandey & Shashi Kant Mishra, 2016. "Duality for Nonsmooth Optimization Problems with Equilibrium Constraints, Using Convexificators," Journal of Optimization Theory and Applications, Springer, vol. 171(2), pages 694-707, November.
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    Cited by:

    1. Le Thanh Tung, 2022. "Karush–Kuhn–Tucker optimality conditions and duality for multiobjective semi-infinite programming with vanishing constraints," Annals of Operations Research, Springer, vol. 311(2), pages 1307-1334, April.
    2. Tamanna Yadav & S. K. Gupta & Sumit Kumar, 2024. "Optimality analysis and duality conditions for a class of conic semi-infinite program having vanishing constraints," Annals of Operations Research, Springer, vol. 340(2), pages 1091-1123, September.
    3. Bhuwan Chandra Joshi & Murari Kumar Roy & Abdelouahed Hamdi, 2024. "On Semi-Infinite Optimization Problems with Vanishing Constraints Involving Interval-Valued Functions," Mathematics, MDPI, vol. 12(7), pages 1-19, March.
    4. Balendu Bhooshan Upadhyay & Arnav Ghosh, 2023. "On Constraint Qualifications for Mathematical Programming Problems with Vanishing Constraints on Hadamard Manifolds," Journal of Optimization Theory and Applications, Springer, vol. 199(1), pages 1-35, October.
    5. Tadeusz Antczak, 2022. "Optimality conditions and Mond–Weir duality for a class of differentiable semi-infinite multiobjective programming problems with vanishing constraints," 4OR, Springer, vol. 20(3), pages 417-442, September.
    6. Ali Sadeghieh & Nader Kanzi & Giuseppe Caristi & David Barilla, 2022. "On stationarity for nonsmooth multiobjective problems with vanishing constraints," Journal of Global Optimization, Springer, vol. 82(4), pages 929-949, April.
    7. Hui Huang & Haole Zhu, 2022. "Stationary Condition for Borwein Proper Efficient Solutions of Nonsmooth Multiobjective Problems with Vanishing Constraints," Mathematics, MDPI, vol. 10(23), pages 1-18, December.

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