Fuzzy computations in risk and decision analysis

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Abstract
This paper describes an algorithm for performing extended algebraic operations such as those encountered in risk and decision analysis under fuzzy conditions. The method makes use of the lambda-cut representations of fuzzy sets and interval analysis. It is an approximate computational technique but is highly efficient compared with the exact method of nonlinear programming, with an accuracy which is much better than the conventional discretization approach. The effectiveness and utility of the procedure are illustrated with examples of fuzzy risk and decision analysis taken from available literature.

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