A multi-objective genetic algorithm for optimisation of energy consumption and shop floor production performance
- Submitting institution
-
University of Glasgow
- Unit of assessment
- 12 - Engineering
- Output identifier
- 12-04897
- Type
- D - Journal article
- DOI
-
10.1016/j.ijpe.2016.06.019
- Title of journal
- International Journal of Production Economics
- Article number
- -
- First page
- 259
- Volume
- 179
- Issue
- -
- ISSN
- 0925-5273
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2016
- URL
-
http://eprints.gla.ac.uk/145044/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- A multi-objective genetic algorithm based on NSGA-II is implemented as a model to optimise total electricity consumption and process flow, contributing to the funding of the Industry 4.0 project (EU-PERForM, 680435) on Production harmonizEd Reconfiguration of Flexible Robots and Machinery. The algorithm has since been applied to a robot manufacturing plant in GKN Aerospace Sweden AB and has resulted in reductions in job completion times and more efficient energy use.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
