Use of genetic algorithms in operations management. Part II - Results.

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dc.contributor.authorStockton, Daviden
dc.contributor.authorQuinn, L. (Liam)en
dc.contributor.authorKhalil, R. A. (Riham A.)en
dc.date.accessioned2008-11-24T14:08:00Z
dc.date.available2008-11-24T14:08:00Z
dc.date.issued2004-01-01en
dc.descriptionThe insight gained into the relationship between genetic algorithm (GA) structure and optimisation performance, through the research reported in this paper, provided the knowledge to integrate GAs with discrete event simulation which formed the output from IMI EPSRC Project GR/N05871 ‘Responsive Design and Operation of Flexible Machining Lines’ rated by EPSRC as “Tending to Internationally Leading” where industrial partners included Neil_R_Smith@unipart.co.uk, Unipart Group Ltd and Nigel.Shires@preactor.com, Preactor International. The author was Principal Investigator for the project.en
dc.identifier.citationStockton, D.J., Quinn, L. and Khalil, R.A. (2004) Use of genetic algorithms in operations management. Part II - Results. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 218(3), pp. 329-343.
dc.identifier.doihttps://doi.org/10.1243/095440504322984876
dc.identifier.issn0954-4054en
dc.identifier.issn2041-2975
dc.identifier.urihttp://hdl.handle.net/2086/313
dc.language.isoenen
dc.publisherProfessional Engineering Publishingen
dc.researchgroupManufacturing Research
dc.subjectRAE 2008
dc.subjectUoA 28 Mechanical, Aeronautical and Manufacturing Engineering
dc.titleUse of genetic algorithms in operations management. Part II - Results.en
dc.typeArticleen

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