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Solving Large p-median Problems by a Multistage Hybrid Approach Using Demand Points Aggregation and Variable Neighbourhood Search

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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http://dx.doi.org/10.1007/s10898-013-0080-z

Abstract

A hybridisation of a clustering-based technique and of a variable neighbourhood

on a multi-stage methodology where learning from previous stages is taken into account

by a fast procedure to produce good feasible solutions. Within each stage, the solutions

augmented p-median problem is then solved by VNS. As these problems used aggregation,

for each of the ‘aggregation’-based solution. The one yielding the least cost is then selected

several times until a certain criterion is met. This approach is enhanced by an efficient way

to their nearest facilities. The proposed approach is tested, using various values of p, on

results.

Item Type: Article
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: Faculties > Social Sciences > Kent Business School
Faculties > Social Sciences > Kent Business School > Management Science
Faculties > Social Sciences > Kent Business School > Centre for Logistics and Heuristic Organisation (CLHO)
Depositing User: Said Salhi
Date Deposited: 27 Jun 2013 14:12 UTC
Last Modified: 08 Feb 2020 04:04 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/34434 (The current URI for this page, for reference purposes)
Salhi, Said: https://orcid.org/0000-0002-3384-5240
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