Outranking under uncertainty using scenarios

•Describes a scenario-based outranking model for decisions under uncertainty.•Relates the scenario model to existing outranking approaches.•Conducts a simulation study to assess the accuracy of the scenario model.•Finds that the scenario model can give reasonable accuracy in most cases.•A critical aspect is good scenario construction covering possible futures.

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.