Skip to main content

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

Abstract

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.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3

References

  • Barron H, Schmidt P (1988) Sensitivity analysis of additive multi-attribute value models. Oper Res 36(1):122–127

    Article  Google Scholar 

  • Belton V, Stewart TJ (2002) Multiple criteria decision analysis: an integrated approach. Kluwer Academic Publisher, Dordrecht

    Google Scholar 

  • Brans JP, Vincke PH (1985) A preference ranking organisation method: the PROMETHEE method for multiple criteria decision making. Manage Sci 31(6):647–656

    Article  Google Scholar 

  • Critchfield GC, Willard KE (1986) Probabilistic analysis of decision trees using Monte Carlo simulation. Med Decis Making 6(1):85–92

    Article  CAS  Google Scholar 

  • Felli JC, Hazen GB (1998) Sensitivity analysis and the expected value of perfect information. Med Decis Making 18(1):95–109

    Article  CAS  Google Scholar 

  • Gal T, Stewart TJ, Hanne T (eds) (1999) Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory, and Applications, Kluwer

  • Halfon E, Reggiani MG (1986) On ranking chemicals for environmental hazard. Environ Sci Technol 20:1173–1179

    Article  CAS  Google Scholar 

  • Hwang CL, Yoon KS (1981) Multiple attribute decision making: methods and applications. Springer, Berlin

    Google Scholar 

  • Hyde KM, Maier HR, Colby CB (2004) Reliability-based approach to multicriteria decision analysis for water resources. J Water Resour Plan Manage 130(6):429–438

    Article  Google Scholar 

  • Janssen R (1996) Multiobjective decision support for environmental management. Kluwer, Dordrecht, The Netherlands

  • Mousseau V, Figueira J, Dias L, Gomes da Silva C, Climaco J (2003) Resolving inconsistencies among constraints on the parameters of an MCDA model. Eur J Oper Res 147(1):72–93

    Article  Google Scholar 

  • Pettit C, Azapagic A, Jefferis S (2005) A framework for sustainable management of urban pollution. Eng Sustain 158(ES3):163–169

    Google Scholar 

  • Pettit C, Azapagic A, Chalabi Z, Kapelan K, Dorini G (2007) PUrE Risk Workshop Summary Report. Half-day Workshop on: Risk and Uncertainty in Decision Making (held Monday 9th July 2007, Manchester). Joint Report prepared by The University of Manchester, Exeter University and the London School of Hygiene and Tropical Medicine. September 2007

  • Ringuest JL (1997) Lp-metric sensitivity analysis for single and multi-attribute decision analysis. Eur J Oper Res 98:563–570

    Article  Google Scholar 

  • Roy B (1968) Classement et choix en presence de points devue multiples (la methode ELECTRE). Revue d’Informatique et de recherché opérationelle 6(8):57–75

    Google Scholar 

  • Saaty TL (1980) The analytic hierarchy process. McGraw Hill, New York

    Google Scholar 

  • Triantaphyllou E, Sanchez A (1997) A sensitivity analysis approach for some deterministic multi-criteria decision-making methods. Decis Sci 28(1):151–194

    Article  Google Scholar 

  • UKCIP (2003) Climate adaption: risk, uncertainty and decision making. UKCIP, Oxford

  • Wille R (1982) Restructuring lattice theory: an approach based on hierarchies of concepts. In: Rival I (ed) Ordered set. Reidel, Dordrecht–Boston, pp 445–470

  • Zeleny M (1973) Compromise programming. In: Cochrane J, Zeleny M (eds) Multiple criteria decision making. University of South Carolina Press, Columbia, pp 373–391

Download references

Acknowledgements

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.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gianluca Dorini.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

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

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10098-010-0291-7

Keywords