In real life, decisions are usually made by comparing different options with respect to several, often conflicting criteria. This requires subjective judgements on the importance of different criteria by DMs and increases uncertainty in decision making. This article demonstrates how uncertainty can be handled in multi-criteria decision situations using Compromise Programming, one of the Multi-criteria Decision Analysis (MCDA) techniques. Uncertainty is characterised using a probabilistic approach and propagated using a Monte Carlo simulation technique. The methodological approach is illustrated on a case study which compares the sustainability of two options for electricity generation: coal versus biomass. Different models have been used to quantify their sustainability performance for a number of economic, environmental and social criteria. Three cases are considered with respect to uncertainty: (1) no uncertainty, (2) uncertainty in data/models and (3) uncertainty in models and decision-makers’ preferences. The results shows how characterising and propagating uncertainty can help increase the effectiveness of multi-criteria decision making processes and lead to more informed decision.
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This study has been carried out as part of the project “Pollutants in Urban Environment (PUrE)” (grant no. EP/C532651/2), funded by the U.K. Engineering and Physical Sciences Research Council, which is gratefully acknowledged. We are also grateful to the PUrE researchers who have contributed to this study in various ways. The contribution of the PUrE stakeholders is also acknowledged.
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Dorini, G., Kapelan, Z. & Azapagic, A. Managing uncertainty in multiple-criteria decision making related to sustainability assessment. Clean Techn Environ Policy 13, 133–139 (2011). https://doi.org/10.1007/s10098-010-0291-7