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.