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Duality Without a Constraint Qualification for Minimax Fractional Programming

Author

Listed:
  • H. C. Lai

    (I-Shou University)

  • J. C. Liu

    (National Overseas Chinese Student University)

  • K. Tanaka

    (Niigata University)

Abstract

Using a parametric approach, we establish the necessary and sufficient conditions for generalized fractional programming without the need of a constraint qualification. Subsequently, these optimality criteria are utilized as a basis for constructing a parametric dual model and two other parameter-free dual models. Several duality theorems are established.

Suggested Citation

  • H. C. Lai & J. C. Liu & K. Tanaka, 1999. "Duality Without a Constraint Qualification for Minimax Fractional Programming," Journal of Optimization Theory and Applications, Springer, vol. 101(1), pages 109-125, April.
    • Handle: RePEc:spr:joptap:v:101:y:1999:i:1:d:10.1023_a:1021771011210
    DOI: 10.1023/A:1021771011210
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    Cited by:

    1. Jeyakumar, V. & Li, G.Y. & Srisatkunarajah, S., 2013. "Strong duality for robust minimax fractional programming problems," European Journal of Operational Research, Elsevier, vol. 228(2), pages 331-336.
    2. Jin-Chirng Lee & Hang-Chin Lai, 2005. "Parameter-Free Dual Models for Fractional Programming with Generalized Invexity," Annals of Operations Research, Springer, vol. 133(1), pages 47-61, January.
    3. H. C. Lai & T. Y. Huang, 2008. "Minimax Fractional Programming for n-Set Functions and Mixed-Type Duality under Generalized Invexity," Journal of Optimization Theory and Applications, Springer, vol. 139(2), pages 295-313, November.
    4. V. Jeyakumar & J. Vicente-Pérez, 2014. "Dual Semidefinite Programs Without Duality Gaps for a Class of Convex Minimax Programs," Journal of Optimization Theory and Applications, Springer, vol. 162(3), pages 735-753, September.

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