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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, ?, ?, 2020 DOI: 10.1016/j.disopt.2020.100579

    Accepted author manuscript, 445 KB, PDF document

    Embargo ends: 4/03/21

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

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A cut-and-branch algorithm for the quadratic knapsack problem

Research output: Contribution to journalJournal article

E-pub ahead of print
Article number100579
<mark>Journal publication date</mark>4/03/2020
<mark>Journal</mark>Discrete Optimization
Number of pages18
Publication statusE-pub ahead of print
Early online date4/03/20
Original languageEnglish

Abstract

The Quadratic Knapsack Problem (QKP) is a well-known NP-hard combinatorial optimisation problem, with many practical applications. We present a ‘cut-and-branch’ algorithm for the QKP, in which a cutting-plane phase is followed by a branch-and-bound phase. The cutting-plane phase is more sophisticated than the existing ones in the literature, incorporating several classes of cutting planes, two primal heuristics, and several rules for eliminating variables and constraints. Computational results show that the algorithm is competitive.

Bibliographic note

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, ?, ?, 2020 DOI: 10.1016/j.disopt.2020.100579