Use of genetic algorithms in operations management. Part I: Applications.
Date
2004-01-01
Authors
Stockton, David
Quinn, L. (Liam)
Khalil, R. A. (Riham A.)
Journal Title
Journal ISSN
ISSN
0954-4054
2041-2975
2041-2975
Volume Title
Publisher
Professional Engineering Publishing
Peer reviewed
Abstract
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.
Keywords
RAE 2008, UoA 28 Mechanical, Aeronautical and Manufacturing Engineering
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