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Outranking under uncertainty using scenarios

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  • Durbach, Ian N.

Abstract

This paper considers the use of scenarios to treat uncertain attribute evaluations in the outranking methods. The scenario-based approach allows the decision maker to think deterministically about the problem by attaching causal links to a small number of potential outcomes, instead of using probability distributions. The scenario approach can be expressed as a simplified version of the comprehensive but practically complex “distributive” outranking method of d’Avignon and Vincke. Using a scenario approach has distinct practical advantages, but also presents the inherent danger that meaningful information is ignored. The extent of this danger is assessed using a simulation experiment, where it is found to be of a magnitude that is non-trivial but still potentially acceptable for certain decision contexts.

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  • Durbach, Ian N., 2014. "Outranking under uncertainty using scenarios," European Journal of Operational Research, Elsevier, vol. 232(1), pages 98-108.
    • Handle: RePEc:eee:ejores:v:232:y:2014:i:1:p:98-108
    DOI: 10.1016/j.ejor.2013.06.041
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    Cited by:

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    2. Helena Gaspars-Wieloch, 2021. "The Assignment Problem in Human Resource Project Management under Uncertainty," Risks, MDPI, vol. 9(1), pages 1-17, January.
    3. Katsikopoulos, Konstantinos V. & Durbach, Ian N. & Stewart, Theodor J., 2018. "When should we use simple decision models? A synthesis of various research strands," Omega, Elsevier, vol. 81(C), pages 17-25.
    4. Ian Durbach, 2019. "Scenario planning in the analytic hierarchy process," Futures & Foresight Science, John Wiley & Sons, vol. 1(2), June.

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