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    Rights statement: This is the author’s version of a work that was accepted for publication in Discrete Optimization. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Discrete Optimization, 41, 2021 DOI: 10.1016/j.disopt.2021.100661

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Valid inequalities for quadratic optimisation with domain constraints

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Valid inequalities for quadratic optimisation with domain constraints. / Galli, Laura; Letchford, Adam.

In: Discrete Optimization, Vol. 41, 100661, 31.08.2021.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Galli L, Letchford A. Valid inequalities for quadratic optimisation with domain constraints. Discrete Optimization. 2021 Aug 31;41:100661. Epub 2021 Jul 31. doi: 10.1016/j.disopt.2021.100661

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Galli, Laura ; Letchford, Adam. / Valid inequalities for quadratic optimisation with domain constraints. In: Discrete Optimization. 2021 ; Vol. 41.

Bibtex

@article{15893d0bb79c41629361681350a4e41c,
title = "Valid inequalities for quadratic optimisation with domain constraints",
abstract = "In 2013, Buchheim and Wiegele introduced a quadratic optimisation problem, in which the domain of each variable is a closed subset of the reals. This problem includes several other important problems as special cases. We study some convex sets and polyhedra associated with the problem, and derive several families of strong valid inequalities. We also present some encouraging computational results, obtained by applying our inequalities to (a) integer quadratic programs with box constraints and (b) portfolio optimisation problems with semi-continuous variables.",
keywords = "mixed-integer nonlinear programming, global optimisation, cutting planes",
author = "Laura Galli and Adam Letchford",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in Discrete Optimization. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Discrete Optimization, 41, 2021 DOI: 10.1016/j.disopt.2021.100661",
year = "2021",
month = aug,
day = "31",
doi = "10.1016/j.disopt.2021.100661",
language = "English",
volume = "41",
journal = "Discrete Optimization",
issn = "1572-5286",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Valid inequalities for quadratic optimisation with domain constraints

AU - Galli, Laura

AU - Letchford, Adam

N1 - This is the author’s version of a work that was accepted for publication in Discrete Optimization. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Discrete Optimization, 41, 2021 DOI: 10.1016/j.disopt.2021.100661

PY - 2021/8/31

Y1 - 2021/8/31

N2 - In 2013, Buchheim and Wiegele introduced a quadratic optimisation problem, in which the domain of each variable is a closed subset of the reals. This problem includes several other important problems as special cases. We study some convex sets and polyhedra associated with the problem, and derive several families of strong valid inequalities. We also present some encouraging computational results, obtained by applying our inequalities to (a) integer quadratic programs with box constraints and (b) portfolio optimisation problems with semi-continuous variables.

AB - In 2013, Buchheim and Wiegele introduced a quadratic optimisation problem, in which the domain of each variable is a closed subset of the reals. This problem includes several other important problems as special cases. We study some convex sets and polyhedra associated with the problem, and derive several families of strong valid inequalities. We also present some encouraging computational results, obtained by applying our inequalities to (a) integer quadratic programs with box constraints and (b) portfolio optimisation problems with semi-continuous variables.

KW - mixed-integer nonlinear programming

KW - global optimisation

KW - cutting planes

U2 - 10.1016/j.disopt.2021.100661

DO - 10.1016/j.disopt.2021.100661

M3 - Journal article

VL - 41

JO - Discrete Optimization

JF - Discrete Optimization

SN - 1572-5286

M1 - 100661

ER -