An exact cutting plane method for the Euclidean max-sum diversity problem

This paper aims to answer an open question recently posed in the literature, that is to find a fast exact method for solving the max-sum diversity problem, a nonconcave quadratic binary maximization problem. We show that, for Euclidean max-sum diversity problems (EMSDP), the distance matrix defining...

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Main Authors: Spiers, Sandy, Bui, Hoa, Loxton, Ryan
Format: Journal Article
Published: 2023
Online Access:http://purl.org/au-research/grants/arc/IC180100030
http://hdl.handle.net/20.500.11937/96042
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author Spiers, Sandy
Bui, Hoa
Loxton, Ryan
author_facet Spiers, Sandy
Bui, Hoa
Loxton, Ryan
author_sort Spiers, Sandy
building Curtin Institutional Repository
collection Online Access
description This paper aims to answer an open question recently posed in the literature, that is to find a fast exact method for solving the max-sum diversity problem, a nonconcave quadratic binary maximization problem. We show that, for Euclidean max-sum diversity problems (EMSDP), the distance matrix defining the quadratic term is always conditionally negative definite. This interesting property ensures that the cutting plane method is exact for (EMSDP), even in the absence of concavity. As such, the cutting plane method, which is primarily designed for concave maximisation problems, converges to the optimal solution of (EMDSP). The method was evaluated on several standard benchmark test sets, where it was shown to outperform other exact solution methods for (EMSDP), and is capable of solving two-coordinate problems of up to eighty-five thousand variables.
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spelling curtin-20.500.11937-960422024-11-08T01:26:43Z An exact cutting plane method for the Euclidean max-sum diversity problem Spiers, Sandy Bui, Hoa Loxton, Ryan This paper aims to answer an open question recently posed in the literature, that is to find a fast exact method for solving the max-sum diversity problem, a nonconcave quadratic binary maximization problem. We show that, for Euclidean max-sum diversity problems (EMSDP), the distance matrix defining the quadratic term is always conditionally negative definite. This interesting property ensures that the cutting plane method is exact for (EMSDP), even in the absence of concavity. As such, the cutting plane method, which is primarily designed for concave maximisation problems, converges to the optimal solution of (EMDSP). The method was evaluated on several standard benchmark test sets, where it was shown to outperform other exact solution methods for (EMSDP), and is capable of solving two-coordinate problems of up to eighty-five thousand variables. 2023 Journal Article http://hdl.handle.net/20.500.11937/96042 10.1016/j.ejor.2023.05.014 http://purl.org/au-research/grants/arc/IC180100030 https://creativecommons.org/licenses/by-nc-nd/4.0/ fulltext
spellingShingle Spiers, Sandy
Bui, Hoa
Loxton, Ryan
An exact cutting plane method for the Euclidean max-sum diversity problem
title An exact cutting plane method for the Euclidean max-sum diversity problem
title_full An exact cutting plane method for the Euclidean max-sum diversity problem
title_fullStr An exact cutting plane method for the Euclidean max-sum diversity problem
title_full_unstemmed An exact cutting plane method for the Euclidean max-sum diversity problem
title_short An exact cutting plane method for the Euclidean max-sum diversity problem
title_sort exact cutting plane method for the euclidean max-sum diversity problem
url http://purl.org/au-research/grants/arc/IC180100030
http://hdl.handle.net/20.500.11937/96042