Quadratic cost flow and the conjugate gradient method

Jie Sun, Xiaoqi Yang, Xiongda Chen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

9 Citations (Scopus)


By introducing quadratic penalty terms, a convex non-separable quadratic network program can be reduced to an unconstrained optimization problem whose objective function is a piecewise quadratic and continuously differentiable function. A conjugate gradient method is applied to the reduced problem and its convergence is proved. The computation exploits the special network data structures originated from the network simplex method. This algorithmic framework allows direct extension to multicommodity cost flows. Some preliminary computational results are presented.
Original languageEnglish
Pages (from-to)104-114
Number of pages11
JournalEuropean Journal of Operational Research
Issue number1
Publication statusPublished - 1 Jul 2005


  • Conjugate gradient methods
  • Network quadratic programming

ASJC Scopus subject areas

  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management


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