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This article presents a linear goal programming framework to obtain normalized interval weights from interval fuzzy preference relations (IFPRs). A parameterized transformation equation is put forward to convert a normalized interval weight vector into IFPRs with additive consistency. Based on a linearization approximate relation of the transformation equation, a two-stage linear goal programming...
Priority weights derived from uncertain preference relations are often characterized by interval weights. A key stage in multiple criteria decision making (MCDM) with a hierarchical structure is to aggregate local interval weights into global interval weights. In this paper, a pair of linear programming models is devised to maximize the lower and upper bounds of the aggregated interval value where...
The derivation of priority weights plays an important role in multi criteria decision making (MCDM) with preference relations. In this paper, interval fuzzy numbers are used to capture vagueness and uncertainty in imprecise judgment data by means of interval fuzzy preference relations. The criterion weights or priority weights of decision alternatives are characterized by normalized interval weights...
This article investigates the consistency of interval fuzzy preference relations based on interval arithmetic, and new definitions are introduced for additive consistent, multiplicative consistent and weakly transitive interval fuzzy preference relations. Transformation functions are put forward to convert normalized interval weights into consistent interval fuzzy preference relations. By analyzing...
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