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

Date
2004-01-01
Authors
Stockton, David
Quinn, L. (Liam)
Khalil, R. A. (Riham A.)
Journal Title
Journal ISSN
ISSN
0954-4054
2041-2975
Volume Title
Publisher
Professional Engineering Publishing
Peer reviewed
Abstract
Description
The 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.
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 II - Results. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 218(3), pp. 329-343.
Research Institute