Irawan, Chandra A., Salhi, Said (2015) Solving Large p-median Problems by a Multistage Hybrid Approach Using Demand Points Aggregation and Variable Neighbourhood Search. Journal of Global Optimization, 63 . pp. 537-554. ISSN 0925-5001. (doi:10.1007/s10898-013-0080-z) (KAR id:34434)
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Official URL: http://dx.doi.org/10.1007/s10898-013-0080-z |
Abstract
A hybridisation of a clustering-based technique and of a variable neighbourhood
search (VNS) is designed to solve large-scale p-median problems. The approach is based
on a multi-stage methodology where learning from previous stages is taken into account
when tackling the next stage. Each stage is made up of several subproblems that are solved
by a fast procedure to produce good feasible solutions. Within each stage, the solutions
returned are put together to make up a new promising subset of potential facilities. This
augmented p-median problem is then solved by VNS. As these problems used aggregation,
a cost evaluation based on the original demand points instead of aggregation is computed
for each of the ‘aggregation’-based solution. The one yielding the least cost is then selected
and its chosen facilities included into the next stages. This multi-stage process is repeated
several times until a certain criterion is met. This approach is enhanced by an efficient way
to aggregate the data and a neighbourhood reduction scheme when allocating demand points
to their nearest facilities. The proposed approach is tested, using various values of p, on
the largest data sets from the literature with up to 89,600 demand points with encouraging
results.
Item Type: | Article |
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DOI/Identification number: | 10.1007/s10898-013-0080-z |
Uncontrolled keywords: | Variable neighbourhood search · Location problem · Aggregation · p-median |
Subjects: |
H Social Sciences H Social Sciences > HA Statistics > HA33 Management Science |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Said Salhi |
Date Deposited: | 27 Jun 2013 14:12 UTC |
Last Modified: | 19 Sep 2023 15:04 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/34434 (The current URI for this page, for reference purposes) |
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