Multivariate Gaussian criteria in SMAA

Risto Lahdelma*, Simo Makkonen, Pekka Salminen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

46 Citations (Scopus)


We consider stochastic multicriteria decision-making problems with multiple decision makers. In such problems, the uncertainty or inaccuracy of the criteria measurements and the partial or missing preference information can be represented through probability distributions. In many real-life problems the uncertainties of criteria measurements may be dependent. However, it is often difficult to quantify these dependencies. Also, most of the existing methods are unable to handle such dependency information. In this paper, we develop a method for handling dependent uncertainties in stochastic multicriteria group decision-making problems. We measure the criteria, their uncertainties and dependencies using a stochastic simulation model. The model is based on decision variables and stochastic parameters with given distributions. Based on the simulation results, we determine for the criteria measurements a joint probability distribution that quantifies the uncertainties and their dependencies. We then use the SMAA-2 stochastic multicriteria acceptability analysis method for comparing the alternatives based on the criteria distributions. We demonstrate the use of the method in the context of a strategic decision support model for a retailer operating in the liberated European electricity market.

Original languageEnglish
Pages (from-to)957-970
Number of pages14
JournalEuropean Journal of Operational Research
Issue number3
Publication statusPublished - 1 May 2006
MoE publication typeA1 Journal article-refereed


  • Energy market modelling
  • Multicriteria decision support
  • Optimisation
  • Risk analysis
  • Simulation

Fingerprint Dive into the research topics of 'Multivariate Gaussian criteria in SMAA'. Together they form a unique fingerprint.

Cite this