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    Rights statement: This is the author’s version of a work that was accepted for publication in Operations Research Letters. 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 Operations Research Letters, 46, 5, 2018 DOI: 10.1016/j.orl.2018.08.005

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A binarisation heuristic for non-convex quadratic programming with box constraints

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A binarisation heuristic for non-convex quadratic programming with box constraints. / Galli, Laura; Letchford, Adam Nicholas.
In: Operations Research Letters, Vol. 46, No. 5, 01.09.2018, p. 529-533.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Galli L, Letchford AN. A binarisation heuristic for non-convex quadratic programming with box constraints. Operations Research Letters. 2018 Sept 1;46(5):529-533. Epub 2018 Aug 30. doi: 10.1016/j.orl.2018.08.005

Author

Galli, Laura ; Letchford, Adam Nicholas. / A binarisation heuristic for non-convex quadratic programming with box constraints. In: Operations Research Letters. 2018 ; Vol. 46, No. 5. pp. 529-533.

Bibtex

@article{b50ec455ffe942878a525fae57ee53ab,
title = "A binarisation heuristic for non-convex quadratic programming with box constraints",
abstract = "Non-convex quadratic programming with box constraints is a fundamental problem in the global optimization literature, being one of the simplest NP-hard nonlinear programs. We present a new heuristic for this problem, which enables one to obtain solutions of excellent quality in reasonable computing times. The heuristic consists of four phases: binarisation, convexification, branch-and-Bound, and local optimisation. Some very encouraging computational results are given.",
keywords = "global optimisation, heuristics, integer programming",
author = "Laura Galli and Letchford, {Adam Nicholas}",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in Operations Research Letters. 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 Operations Research Letters, 46, 5, 2018 DOI: 10.1016/j.orl.2018.08.005",
year = "2018",
month = sep,
day = "1",
doi = "10.1016/j.orl.2018.08.005",
language = "English",
volume = "46",
pages = "529--533",
journal = "Operations Research Letters",
issn = "0167-6377",
publisher = "Elsevier",
number = "5",

}

RIS

TY - JOUR

T1 - A binarisation heuristic for non-convex quadratic programming with box constraints

AU - Galli, Laura

AU - Letchford, Adam Nicholas

N1 - This is the author’s version of a work that was accepted for publication in Operations Research Letters. 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 Operations Research Letters, 46, 5, 2018 DOI: 10.1016/j.orl.2018.08.005

PY - 2018/9/1

Y1 - 2018/9/1

N2 - Non-convex quadratic programming with box constraints is a fundamental problem in the global optimization literature, being one of the simplest NP-hard nonlinear programs. We present a new heuristic for this problem, which enables one to obtain solutions of excellent quality in reasonable computing times. The heuristic consists of four phases: binarisation, convexification, branch-and-Bound, and local optimisation. Some very encouraging computational results are given.

AB - Non-convex quadratic programming with box constraints is a fundamental problem in the global optimization literature, being one of the simplest NP-hard nonlinear programs. We present a new heuristic for this problem, which enables one to obtain solutions of excellent quality in reasonable computing times. The heuristic consists of four phases: binarisation, convexification, branch-and-Bound, and local optimisation. Some very encouraging computational results are given.

KW - global optimisation

KW - heuristics

KW - integer programming

U2 - 10.1016/j.orl.2018.08.005

DO - 10.1016/j.orl.2018.08.005

M3 - Journal article

VL - 46

SP - 529

EP - 533

JO - Operations Research Letters

JF - Operations Research Letters

SN - 0167-6377

IS - 5

ER -