Alternative Mixed Integer Linear Programming Formulations for Globally Solving Standard Quadratic Programs
Abstract
Standard quadratic programs have numerous applications and play an important role in copositivity detection. We consider reformulating a standard quadratic program as a mixed integer linear programming (MILP) problem. We propose alternative MILP reformulations that exploit the specific structure of standard quadratic programs. We report extensive computational results on various classes of instances. Our experiments reveal that our MILP reformulations significantly outperform other global solution approaches.
This is joint work with Jacek Gondzio.