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

Becky Callaghan, Said Salhi and Jack Brimberg

Journal of the Operational Research Society, 2019, vol. 70, issue 2, 192-211

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$ \alpha $-neighbour p-centre problem and the conditional p-centre problem. A scenario analysis using variable α$ \alpha $ is also performed to provide further managerial insights.

Date: 2019
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DOI: 10.1080/01605682.2017.1421854

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