A simulated annealing algorithm for joint stratification and sample allocation

Simple item page
dc.contributor.authorO'Luing, Mervyn
dc.contributor.authorPrestwich, Steven D.
dc.contributor.authorTarim, S. Armagan
dc.contributor.funderScience Foundation Irelanden
dc.contributor.funderEuropean Regional Development Funden
dc.date.accessioned2023-01-11T14:23:21Z
dc.date.available2023-01-11T14:23:21Z
dc.date.issued2022-06-21
dc.date.updated2023-01-11T14:14:38Z
dc.description.abstractThis study combines simulated annealing with delta evaluation to solve the joint stratification and sample allocation problem. In this problem, atomic strata are partitioned into mutually exclusive and collectively exhaustive strata. Each partition of atomic strata is a possible solution to the stratification problem, the quality of which is measured by its cost. The Bell number of possible solutions is enormous, for even a moderate number of atomic strata, and an additional layer of complexity is added with the evaluation time of each solution. Many larger scale combinatorial optimisation problems cannot be solved to optimality, because the search for an optimum solution requires a prohibitive amount of computation time. A number of local search heuristic algorithms have been designed for this problem but these can become trapped in local minima preventing any further improvements. We add, to the existing suite of local search algorithms, a simulated annealing algorithm that allows for an escape from local minima and uses delta evaluation to exploit the similarity between consecutive solutions, and thereby reduces the evaluation time. We compared the simulated annealing algorithm with two recent algorithms. In both cases, the simulated annealing algorithm attained a solution of comparable quality in considerably less computation time.en
dc.description.sponsorshipScience Foundation Ireland (SFI Grant No. 12/RC/2289-P2 which is co-funded under the European Regional; SFI Grant number 16/RC/3918 which is co-funded under the European Regional Development Fund)en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationO'Luing, M., Prestwich, S. and Tarim, A. (2022) ‘A simulated annealing algorithm for joint stratification and sample allocation’, Survey Methodology, 48 (1), pp. 225-249. Available at http://www.statcan.gc.ca/pub/12-001-x/2022001/article/00010-eng.htmen
dc.identifier.endpage249en
dc.identifier.issn1492-0921
dc.identifier.issued1en
dc.identifier.journaltitleSurvey Methodologyen
dc.identifier.startpage225en
dc.identifier.urihttps://hdl.handle.net/10468/14042
dc.identifier.volume48en
dc.language.isoenen
dc.publisherStatistics Canadaen
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/en
dc.relation.urihttp://www.statcan.gc.ca/pub/12-001-x/2022001/article/00010-eng.htm
dc.subjectSimulated annealing algorithmen
dc.subjectOptimal stratificationen
dc.subjectSample allocationen
dc.subjectR softwareen
dc.titleA simulated annealing algorithm for joint stratification and sample allocationen
dc.typeArticle (peer-reviewed)en
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
00010-eng.pdf
Size:
756.52 KB
Format:
Adobe Portable Document Format
Description:
Published version
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
2.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Computer Science - Journal Articles
Insight Centre for Data Analytics - Journal Articles