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A Novel Optimization Method for Nonconvex Quadratically Constrained Quadratic Programs

Author

Listed:
  • Hongwei Jiao
  • Yong-Qiang Chen
  • Wei-Xin Cheng

Abstract

This paper presents a novel optimization method for effectively solving nonconvex quadratically constrained quadratic programs (NQCQP) problem. By applying a novel parametric linearizing approach, the initial NQCQP problem and its subproblems can be transformed into a sequence of parametric linear programs relaxation problems. To enhance the computational efficiency of the presented algorithm, a cutting down approach is combined in the branch and bound algorithm. By computing a series of parametric linear programs problems, the presented algorithm converges to the global optimum point of the NQCQP problem. At last, numerical experiments demonstrate the performance and computational superiority of the presented algorithm.

Suggested Citation

  • Hongwei Jiao & Yong-Qiang Chen & Wei-Xin Cheng, 2014. "A Novel Optimization Method for Nonconvex Quadratically Constrained Quadratic Programs," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnlaaa:v:2014:y:2014:i:1:n:698489
    DOI: 10.1155/2014/698489
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    References listed on IDEAS

    as
    1. Hongwei Jiao & Yongqiang Chen, 2013. "A Global Optimization Algorithm for Generalized Quadratic Programming," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-9, October.
    2. Hongwei Jiao & Yongqiang Chen, 2013. "A Global Optimization Algorithm for Generalized Quadratic Programming," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
    3. Eric V. Denardo & Christopher S. Tang, 1992. "Linear Control of a Markov Production System," Operations Research, INFORMS, vol. 40(2), pages 259-278, April.
    4. Andrés Weintraub & Jorge Vera, 1991. "A Cutting Plane Approach for Chance Constrained Linear Programs," Operations Research, INFORMS, vol. 39(5), pages 776-785, October.
    Full references (including those not matched with items on IDEAS)

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