Issue |
Radioprotection
Volume 55, May 2020
Coping with uncertainties for improved modelling and decision making in nuclear emergencies. Key results of the CONFIDENCE European research project
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Page(s) | S181 - S185 | |
Section | DECISION MAKING UNDER UNCERTAINTIES | |
DOI | https://doi.org/10.1051/radiopro/2020030 | |
Published online | 01 May 2020 |
Article
MCDA handling uncertainties
KIT – Karlsruhe Institute of Technology,
Eggenstein-Leopoldshafen, Germany
* Corresponding author: tim.mueller@kit.edu
Work package 6 (WP) of the European project CONFIDENCE focussed on decision support for stakeholders in nuclear emergencies especially considering uncertainties in such scenarios. A well-suited method for collaborative decision support is the Multi Criteria Decision Analysis (MCDA). It provides a transparent approach for choosing a suitable strategy from a pool of strategies taking into account the different preferences of the involved stakeholders. One goal of WP 6 was to provide this method as a software tool to the nuclear emergency management community. However a default MCDA is not capable of handling uncertainties as input parameters. We embedded an existing MCDA tool in an ensemble evaluation framework to overcome this limitation and to process probabilistic input parameters. Within this framework random deterministic MCDAs are generated from the probabilistic MCDA and their results are combined into a single result reflecting this uncertainty. The enhanced MCDA tool provides user interfaces for defining probabilistic input parameters for impact values and criteria weights, as well as graphical components to communicate the results to the stakeholders. The tool was presented in several workshops to the potential stakeholders where it was applied to fictitious scenarios. The feedback was used to improve the tool in several iterations.
Key words: uncertainties / multi criteria decision analysis / uncertainty / ensemble evaluation / CONFIDENCE
© The Authors, published by EDP Sciences 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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