The work deals with a recognition problem using a probabilistic-fuzzy model and multistage decision logic. A case where a loss function is described using fuzzy numbers has been considered. The globally optimal Bayes strategy has been calculated for this case with stage-dependent and dependent on the node of the decision tree fuzzy loss function. The obtained result is illustrated by a calculat...

Recently Abbasbandy and Hajjari (Computers and Mathematics with Applications57 (2009) 413-419) have introduced a ranking method for the trapezoidalfuzzy numbers. This paper extends theirs method to all fuzzy numbers,which uses from a defuzzication of fuzzy numbers and a general weightingfunction. Extended method is interesting for ranking all fuzzy numbers, and itcan be applied for solving and ...

This paper conducts a comparison analysis of some of the most common defuzzification techniques which helps rank fuzzy weights calculated from fuzzy comparison matrices through Fuzzy Analytic Hierarchy Process. Ranking of weights calculated through FAHP algorithms is of critical importance as it directly effects the decision making process. More so ranking of fuzzy numbers is also important in ...

generally, an engineering design problem has multiple objective functions. some of these problems can be formulated as multiobjective geometric programming models. on the other hand,often in the real world, coefficients of the objective functions are not known precisely. coefficients may be interpreted as fuzzy numbers, which lead to a multiobjective geometric programming with fuzzy parameters....

The importance and difficulty of the problem of ranking fuzzy numbers is pointed out. Here we consider approaches to the ranking of fuzzy numbers based upon the idea of associating with a fuzzy number a scalar value, its valuation, and using this valuation to compare and order fuzzy numbers. Specifically we focus on expected value type valuations which are based upon the transformation of a fuz...

Two existing methods for solving fuzzy variable linear programming problems based on ranking functions are the fuzzy primal simplex method proposed by Mahdavi-Amiri et al. (2009) and the fuzzy dual simplex method proposed by Mahdavi-Amiri and Nasseri (2007). In this paper, we prove that in the absence of degeneracy these fuzzy methods stop in a finite number of iterations. Moreover, we generali...

One of the most important reasons for information systems failure is lack of quality. Information Systems Quality (ISQ) evaluation is important to prevent the lack of quality. ISQ evaluation is one of the most important Multi-Criteria Decision Making (MCDM) problems. The concept of Single Valued Triangular Neutrosophic Numbers (SVTrN-numbers) is a generalization of fuzzy set and intuitionistic ...

This chapter describes different methods for comparing and ordering fuzzy numbers. Theoretically, fuzzy numbers can only be partially ordered, and hence cannot be compared. However, in practical applications, such as decision making, scheduling, market analysis or optimisation with fuzzy uncertainties, the comparison of fuzzy numbers becomes crucial. Theoretically, fuzzy numbers can only be par...

The TODIM is a valuable technique for solving classical MCDM problems in case of considering the decision maker’s psychological behavior. One main goal of this chapter is to introduce the measured functions-based hesitant fuzzy TODIM technique to deal with the behavioral MCDM problem under hesitant fuzzy environments. The main advantages of this technique are that (1) it can handle the MCDM pro...

supplier selection is a multi-criteria problem. this study proposes a hybrid model for supporting the suppliers’ selection and ranking. this research is a two-stage model designed to fully rank the suppliers where each supplier has multiple inputs and outputs. first, the supplier evaluation problem is formulated by data envelopment analysis (dea), since the regarded decision deals with uncertai...