Online optimization of casualty processing in major incident response: An experimental analysis
- Submitting institution
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City, University of London
- Unit of assessment
- 12 - Engineering
- Output identifier
- 401
- Type
- D - Journal article
- DOI
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10.1016/j.ejor.2016.01.021
- Title of journal
- European Journal of Operational Research
- Article number
- -
- First page
- 334
- Volume
- 252
- Issue
- 1
- ISSN
- 0377-2217
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- 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)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper presents an important extension to the author's previously developed major casualty incident (MCI) computational prediction tool (2013). The extension moves the earlier static multi-objective combinatorial optimsation model to incorporate dynamic (online) processing of evolving information from medical responders, fire and rescue personel, hospital operational staff (managing bed allocation) and travel time estimates from live feeds. The approach uses a Markov chain triage model coupled with a variable neighbourhood descent algorithm to search for optimal responder solutions to distribute tasks and thereby minimise suffering and maximise survivability. The London bombings of 07.07.05 illustrate the effectiveness of the new capability
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -