Minimum cost polygon overlay with rectangular shape stock panels

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aut.relation.endpage24
aut.relation.issue3
aut.relation.startpage1
aut.relation.volume4
aut.researcherConnor, Andrew Miles
dc.contributor.authorSiringoringo, WS
dc.contributor.authorConnor, AM
dc.contributor.authorClements, N
dc.contributor.authorAlexander, N
dc.date.accessioned2014-04-12T01:56:27Z
dc.date.available2014-04-12T01:56:27Z
dc.date.copyright2008
dc.date.issued2008
dc.description.abstractMinimum Cost Polygon Overlay (MCPO) is a unique two-dimensional optimization problem that involves the task of covering a polygon shaped area with a series of rectangular shaped panels. This has a number of applications in the construction industry. This work examines the MCPO problem in order to construct a model that captures essential parameters of the problem to be solved automatically using numerical optimization algorithms. Three algorithms have been implemented of the actual optimization task: the greedy search, the Monte Carlo (MC) method, and the Genetic Algorithm (GA). Results are presented to show the relative effectiveness of the algorithms. This is followed by critical analysis of various findings of this research.
dc.identifier.citationInternational Journal of Construction Education & Research, vol.4(3), pp.1 - 24
dc.identifier.doi10.1080/15578770802494516
dc.identifier.urihttps://hdl.handle.net/10292/7101
dc.publisherTaylor & Francis
dc.rightsCopyright © 2008 Taylor & Francis. This is a preprint of an article whose final and definitive form has been published in the International Journal of Construction Education and Research and is available online at: www.tandfonline.com with the open URL of your article (see Publisher’s Version).
dc.rights.accessrightsOpenAccess
dc.subjectGenetic algorithms
dc.subjectLayout optimization
dc.titleMinimum cost polygon overlay with rectangular shape stock panels
dc.typeJournal Article
pubs.elements-id42934
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/Design & Creative Technologies/Interdisplinary Unit
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