Author(s)

Elias Munapo¹, Santosh Kumar^2*

¹Graduate School of Business and Leadership, University of KwaZulu-Natal, Westville Campus, Durban, South Africa.
²Department of Mathematics and Statistics, University of Melbourne, Parkville, Australia.

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.

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

Munapo, E. and Kumar, S. (2015) A New Heuristic for the Convex Quadratic Programming Problem. American Journal of Operations Research, 5, 373-383. doi: 10.4236/ajor.2015.55031.