Use of genetic algorithms in operations management. Part I: Applications.

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dc.contributor.author Stockton, David en
dc.contributor.author Quinn, L. (Liam) en
dc.contributor.author Khalil, R. A. (Riham A.) en
dc.date.accessioned 2008-11-24T14:07:59Z
dc.date.available 2008-11-24T14:07:59Z
dc.date.issued 2004-01-01 en
dc.identifier.citation Stockton, D.J., Quinn, L. and Khalil, R.A. (2004) Use of genetic algorithms in operations management. Part I: Applications. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture, 218(3), pp. 315-327
dc.identifier.issn 0954-4054 en
dc.identifier.issn 2041-2975 (Online)
dc.identifier.uri http://hdl.handle.net/2086/312
dc.description This output reports application solutions being further advanced and exploited as part of two DTI Technology Programme research projects, ie (i) £1.4 million H0254E ‘Improving customer demand and cost forecasting methods’ where industrial partners include Ian_Warburton@unipart.co.uk, Unipart Logistics and richard.twigg@trelleborg.com, Trelleborg Industrial AVS, and (ii) £1.0 million K1532G ‘Accelerated Process Excellence using Virtual Discrete Event Process Simulation’ where industrial partners include Gillis_Cliff_M@perkins.com, Perkins Engines Group Ltd and keith.higham@intier.com, Intier Automotive Interiors. The author is Principal Investigator for both projects. en
dc.language.iso en en
dc.publisher Professional Engineering Publishing en
dc.subject RAE 2008
dc.subject UoA 28 Mechanical, Aeronautical and Manufacturing Engineering
dc.title Use of genetic algorithms in operations management. Part I: Applications. en
dc.type Article en
dc.identifier.doi http://dx.doi.org/10.1243/095440504322984867 en
dc.researchgroup Manufacturing Research


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