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.

A computational study on QP problems with general linear constraints / Liuzzi, G.; Locatelli, M.; Piccialli, V.. - In: OPTIMIZATION LETTERS. - ISSN 1862-4472. - (2022). [10.1007/s11590-021-01846-6]

A computational study on QP problems with general linear constraints

Liuzzi G.;Piccialli V.
2022

Abstract

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.
2022
Bound tightening; Branch and bound; Linear and convex relaxations; Quadratic programming
01 Pubblicazione su rivista::01a Articolo in rivista
A computational study on QP problems with general linear constraints / Liuzzi, G.; Locatelli, M.; Piccialli, V.. - In: OPTIMIZATION LETTERS. - ISSN 1862-4472. - (2022). [10.1007/s11590-021-01846-6]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1611233
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