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Optimal solutions for the continuous p-centre problem and related α-neighbour and conditional problems: A relaxation-based algorithm

Callaghan, Becky, Salhi, Said, Brimberg, Jack (2019) Optimal solutions for the continuous p-centre problem and related α-neighbour and conditional problems: A relaxation-based algorithm. Journal of the Operational Research Society, 70 (2). pp. 192-211. ISSN 0160-5682. (doi:10.1080/01605682.2017.1421854)

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https://doi.org/10.1080/01605682.2017.1421854

Abstract

This paper aims to solve large continuous p-centre problems optimally by re-examining a recent relaxation-based algorithm. The algorithm is strengthened by adding four mathematically supported enhancements to improve its efficiency. This revised relaxation algorithm yields a massive reduction in computational time enabling for the first time larger data-sets to be solved optimally (e.g., up to 1323 nodes). The enhanced algorithm is also shown to be flexible as it can be easily adapted to optimally solve related practical location problems that are frequently faced by senior management when making strategic decisions. These include the α-neighbour p-centre problem and the conditional p-centre problem. A scenario analysis using variable α is also performed to provide further managerial insights.

Item Type: Article
DOI/Identification number: 10.1080/01605682.2017.1421854
Uncontrolled keywords: Location, p-centre problem, α-neighbourhood, conditional, continuous space, relaxation method, optimal solutions, managerial insights
Subjects: H Social Sciences
Divisions: Faculties > Social Sciences > Kent Business School > Centre for Logistics and Heuristic Organisation (CLHO)
Depositing User: Said Salhi
Date Deposited: 13 Feb 2018 11:21 UTC
Last Modified: 15 Jul 2019 07:48 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/66010 (The current URI for this page, for reference purposes)
Salhi, Said: https://orcid.org/0000-0002-3384-5240
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