In this paper we consider Quadratic Programming (QP) problems with general linear constraints. We show, through a computational investigation, that a careful selection of a suitable reformulation of such problems, together with the related relaxation, and an intensive application of bound tightening are simple but very effective ingredients in order to make a standard branch and bound approach very competitive and in some cases able to outperform even well known commercial solvers.
Dettaglio pubblicazione
2022, OPTIMIZATION LETTERS, Pages -
A computational study on QP problems with general linear constraints (01a Articolo in rivista)
Liuzzi G., Locatelli M., Piccialli V.
Gruppo di ricerca: Continuous Optimization
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