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Penalty Parameter for Linearly Constrained 0–1 Quadratic Programming

Author

Listed:
  • W. X. Zhu

    (Fuzhou University
    Institute of Software, Chinese Academy of Sciences)

Abstract

A linearly constrained 0–1 quadratic programming problem is proved to be equivalent to a continuous concave quadratic problem with an easily computed penalty parameter. Moreover, it is proved that the feasibility of the former problem can be checked by solving the latter.

Suggested Citation

  • W. X. Zhu, 2003. "Penalty Parameter for Linearly Constrained 0–1 Quadratic Programming," Journal of Optimization Theory and Applications, Springer, vol. 116(1), pages 229-239, January.
    • Handle: RePEc:spr:joptap:v:116:y:2003:i:1:d:10.1023_a:1022174505886
    DOI: 10.1023/A:1022174505886
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    Cited by:

    1. Marianna De Santis & Sven de Vries & Martin Schmidt & Lukas Winkel, 2022. "A Penalty Branch-and-Bound Method for Mixed Binary Linear Complementarity Problems," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3117-3133, November.
    2. M. Santis & F. Rinaldi, 2012. "Continuous Reformulations for Zero–One Programming Problems," Journal of Optimization Theory and Applications, Springer, vol. 153(1), pages 75-84, April.
    3. Shenshen Gu & Xinyi Chen, 2020. "The Basic Algorithm for the Constrained Zero-One Quadratic Programming Problem with k -diagonal Matrix and Its Application in the Power System," Mathematics, MDPI, vol. 8(1), pages 1-16, January.
    4. S. Lucidi & F. Rinaldi, 2010. "Exact Penalty Functions for Nonlinear Integer Programming Problems," Journal of Optimization Theory and Applications, Springer, vol. 145(3), pages 479-488, June.

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