TY - JOUR

T1 - Managing uncertainty in multiple-criteria decision making related to sustainability assessment

A1 - Dorini,Gianluca Fabio

A1 - Kapelan,Zoran

A1 - Azapagic,Adisa

AU - Dorini,Gianluca Fabio

AU - Kapelan,Zoran

AU - Azapagic,Adisa

PB - Springer

PY - 2011

Y1 - 2011

N2 - 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.

AB - 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.

KW - Monte Carlo simulation

KW - Multi-criteria decision analysis

KW - Sustainability assessment

KW - Compromise programming

KW - Uncertainty analysis

U2 - 10.1007/s10098-010-0291-7

DO - 10.1007/s10098-010-0291-7

JO - Clean Technologies and Environmental Policy

JF - Clean Technologies and Environmental Policy

SN - 1618-954X

IS - 1

VL - 13

SP - 133

EP - 139

ER -