Decisions about most real problems must be made in a complex setting with uncertain, ambiguous and vague information, and imprecise constraints and goals. There are also differences between decision-making at the management level (non-technical decision-makers) and at the engineering level (Opricovic and Tzeng, 2003).
Decision-making in a fuzzy environment has been defined as a decision process in which the goals and/or constraints, but not necessarily the system under consideration, are fuzzy in nature (Bellman and Zadeh, 1970). There are two basic approaches to decision-making in a fuzzy environment: the ‘conventional’ approach where defuzzification is performed at an early stage, and the fuzzy approach where the fuzziness is eliminated at a later stage (Opricovic and Tzeng, 2003).
6.1 Risk Assessment in Information-Poor Systems
Proper evaluation of uncertainties has become a major concern in environmental (Darba et al., 2008) and health risk assessment studies (Kentel and Aral, 2007), where it is usually necessary to incorporate imprecise and incomplete knowledge about the process under consideration.
In practice, there may be insufficient data available for statistical methods to be used for all variables and a hybrid approach based on a combination of statistical and fuzzy methods may be more appropriate (Guyonnet et al., 2003). Consider the case where the risk is an uncertain function of a number of crisp variables Ci and a number of fuzzy variables ...