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Resource allocation when planning for simultaneous disasters
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Doan, Xuan Vinh and Shaw, Duncan (2019) Resource allocation when planning for simultaneous disasters. European Journal of Operational Research, 274 (2). pp. 687-709. doi:10.1016/j.ejor.2018.10.015 ISSN 0377-2217.
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Official URL: https://doi.org/10.1016/j.ejor.2018.10.015
Abstract
This paper uses stochastic optimisation techniques to allocate scarce national resource across eight cities to best respond to three simultaneous disasters happening across these locations. Our first model analyses the risk of not being able to achieve performance targets given resource constraints while our second model analyses the resources needed to meet target performance levels. A third hybrid model (constructed from the first two models) analyses the implications of different financial budgets. Additional sensitivity analysis is performed by looking into different settings of location importance, number of simultaneous disasters, and resource requirements. We reflect on the use of such modelling techniques for these problems and discuss the influence of political aspects of resource allocation which such models cannot address. We also reflect on the need for advanced modelling to recognise the abilities of the users and the availability of realistic assumptions if they are to influence the practices of disaster managers.
Item Type: | Journal Article | ||||||||
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Subjects: | H Social Sciences > HV Social pathology. Social and public welfare Q Science > QA Mathematics |
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Divisions: | Faculty of Social Sciences > Warwick Business School > Operational Research & Management Sciences Faculty of Social Sciences > Warwick Business School |
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Library of Congress Subject Headings (LCSH): | Disaster relief -- Mathematical models, Stochastic analysis, Cities and towns | ||||||||
Journal or Publication Title: | European Journal of Operational Research | ||||||||
Publisher: | Elsevier Science BV | ||||||||
ISSN: | 0377-2217 | ||||||||
Official Date: | 16 April 2019 | ||||||||
Dates: |
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Volume: | 274 | ||||||||
Number: | 2 | ||||||||
Page Range: | pp. 687-709 | ||||||||
DOI: | 10.1016/j.ejor.2018.10.015 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Reuse Statement (publisher, data, author rights): | © 2018, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/. | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Date of first compliant deposit: | 10 October 2018 | ||||||||
Date of first compliant Open Access: | 13 October 2020 | ||||||||
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