A multi-objective genetic type-2 fuzzy logic based system for mobile field workforce area optimization
- Submitting institution
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The University of Essex
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 3220
- Type
- D - Journal article
- DOI
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10.1016/j.ins.2015.09.014
- Title of journal
- Information Sciences
- Article number
- -
- First page
- 390
- Volume
- 329
- Issue
- -
- ISSN
- 0020-0255
- Open access status
- Out of scope for open access requirements
- Month of publication
- February
- Year of publication
- 2016
- URL
-
-
- 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
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3
- Research group(s)
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A - Artificial Intelligence (AI)
- Citation count
- 31
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Presented novel multi-objective genetic type-2 Fuzzy Logic based system for mobile workforce area optimisation, which was employed by BT. Additional to wide research citations has been in full-use for over five years managing BT's field operations all over the UK. Resulted in increased capacity for more demand leading to improved customer service; a 7% productivity uplift. Helped reduce BT's carbon footprint by 2000metric-tons of CO2/year, savings of 12,500 driving hours every month equivalent to removing over 353 cars off the road per year. Resulted in two PCT patents and won the 2015 and 2017 Global Telecom Business awards (Dr-Gilbert-Owusu,Head-of-Operational-Transformation-Research,Applied-Research,BT-Technology).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
