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Fuzzy modeling of manufacturing and logistic systems. (English) Zbl 1042.90025

The authors present an approach based directly on using fuzzy intervals instead of probability distributions in the simulation procedure. The proposed approach is based on the well defined fuzzy arithmetic rules, but the authors have been faced with the problem of absence of a unique determination of a fuzzy interval comparison procedure. The problem of crisp and fuzzy intervals (numbers) ordering is of everlasting interest, because of its direct relevance in practical modeling and optimization of real world processes. They present a new method of crisp and fuzzy interval comparison (ordering) based on the probabilistic approach, and assume that the fuzzy numbers are represented as ordered \(\alpha\)-level set. The authors note that, the probabilistic approach was used only to infer the set of formula for deterministic quantitative estimation of intervals inequality/equality. Moreover, they present examples illustrating the technique for fuzzy modeling and its comparison with the results of conventional simulation methods.

MSC:

90B50 Management decision making, including multiple objectives
90C70 Fuzzy and other nonstochastic uncertainty mathematical programming
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