The Fuzzyset Approach is based on the premise that traditional crisp boundaries (yes/no, etc.) are inadequate in dealing with risk assessment in real life situations. Gradual memberships of sets in terms of linguistic variables are therefore introduced to make the model intuitively easy to accept, since concepts such as `very high', `moderate' and `low' are quite acceptable terms, and more or less uniformly understood in the parlance of risk assessment. In this article, a multi-objective decision-making model, using the structural forms supplied by the fuzzy set theory ordinal information on preferences, and importance of the individual objectives, has been employed, thereby avoiding the subjectiveness involved in assigning membership functions.

Risk is a function of various factors like, frequency of hazards, probability of a hazardous event taking place, severity of the defined harm caused by the hazard, quantity of release of the hazardous substance, existence of an effective control system, detection ability of the hazardous substance, etc. Moreover, all these factors are not of equal weightage/importance. For example, severity of release of phosgene is very high compared to the high quantity release of chlorine gas. Two primary issues of risk assesment are: (i) to acquire meaningful information regarding the satisfaction of the factors/criteria by various hazards/hazardous events and (ii) to assign relative importance weight to each factor. These issues in many cases, definitely for rare events, are associated with factors like, high level of uncertainty, little previous precedent, variables which are often not scientifically predictable, limited facts and several alternative solutions with good arguments for each. In such situations, intuition is most helpful in making key management decisions7.

The typical multi-objective decision involves the selection of one alternative, ai , from a universe of alternatives A given a collection, or set, say {O}, of objectives of varying importance to the decision maker. It is expected that the overall decision function shall evaluate how well each alternative can satisfy each objective considering their relative importance in some plausible way. In other words, it may be said that this decision function essentially represents a mapping of the alternatives in A to an ordinal set of ranks.

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