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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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    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

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

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published
<mark>Journal publication date</mark>1/09/2018
<mark>Journal</mark>Operations Research Letters
Issue number5
Volume46
Number of pages5
Pages (from-to)529-533
Publication StatusPublished
Early online date30/08/18
<mark>Original language</mark>English

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.

Bibliographic note

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