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R. D. Monteiro, I. Adler and M. G. Resende, “A Polynomial-Time Primal-Dual Affine Scaling Algorithm for Linear and Convex Quadratic Programming and Its Powerseries Extension,” Mathematics of Operations Research, Vol. 15, No. 2, 1990, pp. 191-214. http://dx.doi.org/10.1287/moor.15.2.191

has been cited by the following article:

• TITLE: Fixed-Point Iteration Method for Solving the Convex Quadratic Programming with Mixed Constraints

  AUTHORS: Ruopeng Wang, Hong Shi, Kai Ruan, Xiangyu Gao

  KEYWORDS: Fixed-Point Iteration; Convex Quadratic Programming Problem; Convergence; Smoothing Function

  JOURNAL NAME: Applied Mathematics, Vol.5 No.2, January 20, 2014

  ABSTRACT: The present paper is devoted to a novel smoothing function method for convex quadratic programming problem with mixed constrains, which has important application in mechanics and engineering science. The problem is reformulated as a system of non-smooth equations, and then a smoothing function for the system of non-smooth equations is proposed. The condition of convergences of this iteration algorithm is given. Theory analysis and primary numerical results illustrate that this method is feasible and effective.