comparing the performance of a set of activities or organizations under uncertainty environment has been performed by means of fuzzy data envelopment analysis (fdea) since the traditional dea models require accurate and precise performance data. as regards a method for dealing with uncertainty environment, many researchers have introduced dea models in fuzzy environment. some of these models ar...

Fuzzy data given by expert knowledge can be regarded as a possibility distribution by which possibilistic linear systems are defined. Recently, it has become important to deal with fuzzy data in connection with expert knowledge. Three formulations of possibilistic linear regression analysis are proposed here to deal with fuzzy data. Since our formulations can be reduced to linear programming pr...

Fuzzy systems address the imprecision of the input and output variables, which formally describe notions like “rather warm” or “pretty cold”, while provide a behaviour that depends on fuzzy data. This class of systems are classically represented by means of Fuzzy Inference Systems (FIS), a computing framework based on the concepts of fuzzy if-then rules and fuzzy reasoning. Even if FIS are larg...

As an emerging area considering behavioral aspects of decision making, target-oriented decision model lies in the philosophical root of bounded rationality as well as represents the S-shaped value function. This paper deals with multi-attribute decision analysis from target-oriented viewpoint. First, the basic (random) target-oriented decision model is extended to involve three types of target ...

The suggested approach, FMAA (Fuzzy Multicriteria Acceptability Analysis), assimilates uncertainties/ imprecisions of objective values and subjective judgments within the discrete Multi-Criteria Decision Analysis (MCDA). The presented algorithm for FMAA implementation utilizes fuzzy criterion values and fuzzy weight coefficients based on the use of fuzzy numbers, integral measure to assess the ...

Previous studies have presented correlation analyses among fuzzy attributes. This study proposes a correlation analysis method among crisp attributes and fuzzy attributes to investigate their linear relationships. If A and B are two attributes, A is a nominal-dichotomous attribute, and B is a fuzzy attribute. Thus, identifying the relationship between A and B is possible by using the pointbiser...

In a paper by Chang [D.Y. Chang, Applications of the extent analysis method on fuzzy AHP, European Journal of Operational Research 95 (1996) 649–655], an extent analysis method on fuzzy AHP was proposed to obtain a crisp priority vector from a triangular fuzzy comparison matrix. It is found that the extent analysis method cannot estimate the true weights from a fuzzy comparison matrix and has l...

The fuzzy set theory is being applied massively in many fields these days. One of these is linear programming problems. Kheirfam and Hasani (Sensitivity analysis for fuzzy linear programming problems with fuzzy variables, Advanced Modeling and Optimization, 12 (2010) 257-272), proposed a method for the sensitivity analysis for fuzzy linear programming (FLP) problems with fuzzy variables. There ...

This paper discusses hybrid probabilistic and fuzzy set approaches to propagating randomness and imprecision in risk assessment and fuzzy time series models. Stochastic and Computational Intelligence methods, such as Probability bounds analysis, Fuzzy -levels analysis, Fuzzy random vectors, Wavelets decomposition and Wavelets Networks are combined to capture different kinds of uncertainty. The...