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A canonical dual approach for solving linearly constrained quadratic programs


  • Xing, Wenxun
  • Fang, Shu-Cherng
  • Sheu, Ruey-Lin
  • Wang, Ziteng


This paper provides a canonical dual approach for minimizing a general quadratic function over a set of linear constraints. We first perturb the feasible domain by a quadratic constraint, and then solve a “restricted” canonical dual program of the perturbed problem at each iteration to generate a sequence of feasible solutions of the original problem. The generated sequence is proven to be convergent to a Karush–Kuhn–Tucker point with a strictly decreasing objective value. Some numerical results are provided to illustrate the proposed approach.

Suggested Citation

  • Xing, Wenxun & Fang, Shu-Cherng & Sheu, Ruey-Lin & Wang, Ziteng, 2012. "A canonical dual approach for solving linearly constrained quadratic programs," European Journal of Operational Research, Elsevier, vol. 218(1), pages 21-27.
  • Handle: RePEc:eee:ejores:v:218:y:2012:i:1:p:21-27
    DOI: 10.1016/j.ejor.2011.09.015

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