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dc.contributor.authorWilson, DI
dc.contributor.editorSingamneni, S
dc.date.accessioned2012-12-16T22:53:29Z
dc.date.accessioned2012-12-17T23:00:23Z
dc.date.available2012-12-16T22:53:29Z
dc.date.available2012-12-17T23:00:23Z
dc.date.copyright2012-11-28
dc.date.issued2012-12-17
dc.identifier.citationProceedings of the 11th Global Congress on Manufacturing and Management (GCMM2012) held at AUT, Auckland, New Zealand, 2012-11-28to 2012-11-30, published in: Proceedings of the 11th Global Congress on Manufacturing and Management (GCMM2012), pp.58 - 65 (8)
dc.identifier.isbn978-0-473-23043-2
dc.identifier.urihttp://hdl.handle.net/10292/4932
dc.description.abstractThe continual search for solutions that are better, faster and more efficient is second nature to all engineers. This activity is known as optimisation. But industrial optimisation problems are like the mythical beast, the Jabberwocky; they are big, complex, mean, ill-tempered, and prickly. What is interesting though is how we arrive at optimal solutions; how we can rapidly discard non-contenders, reduce the search-space, and accelerate the passage to the optimum. Essentially how do we optimise the optimisation process? This paper reviews the recent developments in large-scale optimisation algorithms that are suitable for industrial problems. The important issues of correctly formulating the optimisation problem, judging when to add constraints, when to introduce binary variables, and which of the many numerical algorithms to choose are also highlighted with many actual industrial examples such as trajectory planning of the Waiheke ferry, to the optimal operation of steam utility boiler systems, to optimal design of microwave cavities, and the classification of the electrical power usage of suburbs from Dargaville to Wellsford. The take home message is this: With the right tools (many of which are free!), all the world’s problems start to look like optimisation problems where even a slightly better solution is better than nothing at all.
dc.publisherSchool of Engineering, AUT University
dc.relation.replaceshttp://hdl.handle.net/10292/4925
dc.relation.replaces10292/4925
dc.relation.urihttp://www.aut.ac.nz/engineering/gcmm2012
dc.rightsAuckland University of Technology (AUT) encourages public access to AUT information and supports the legal use of copyright material in accordance with the Copyright Act 1994 (the Act) and the Privacy Act 1993. Unless otherwise stated, copyright material contained on this site may be in the intellectual property of AUT, a member of staff or third parties. Any commercial exploitation of this material is expressly prohibited without the written permission of the owner.
dc.subjectOptimisation
dc.subjectAlgorithms
dc.subjectLarge-scale
dc.subjectIndustrial applications
dc.subjectOPTI
dc.titleNavigating the wilds of industrial optimisation
dc.typeConference Contribution
dc.rights.accessrightsOpenAccess
aut.conference.typePaper Published in Proceedings
aut.relation.endpage65
aut.relation.pages8
aut.relation.startpage58
pubs.elements-id132064


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