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Burer, S.D. and Vandenbussche, D. (2009) Globally Solving Box-Constrained Non Convex Quadratic Programs with Semidefinite-Based Finite Branch-and-Bound. Computational Optimisation and Applications, 43, 181-195.

has been cited by the following article:

• TITLE: A New Heuristic for the Convex Quadratic Programming Problem

  AUTHORS: Elias Munapo, Santosh Kumar

  KEYWORDS: Convex Quadratic Programming, Linear Programming, Karush-Kuhn-Tucker Conditions, Simplex Method, Interior Point Method

  JOURNAL NAME: American Journal of Operations Research, Vol.5 No.5, September 2, 2015

  ABSTRACT: This paper presents a new heuristic to linearise the convex quadratic programming problem. The usual Karush-Kuhn-Tucker conditions are used but in this case a linear objective function is also formulated from the set of linear equations and complementarity slackness conditions. An unboundedness challenge arises in the proposed formulation and this challenge is alleviated by construction of an additional constraint. The formulated linear programming problem can be solved efficiently by the available simplex or interior point algorithms. There is no restricted base entry in this new formulation. Some computational experiments were carried out and results are provided.