Ranking fuzzy numbers play a vital role in decision making problems, data analysis and socio economics systems. Ranking fuzzy numbers is a necessary step in many mathematical models. Many of the methods proposed so far are non-discriminating. This paper presents a new ranking method and using which we convert the fuzzy transportation problem to a crisp valuedtransportation problem which then ca...

In this paper, we want to present a new method for ranking exponential fuzzy numbers with use weighted average and weighted width in TRD distance. Weighted average and weighted width of exponential fuzzy numbers combines in TRD distance for ranking method. A simpler and easier approach is proposed for the ranking of generalized trapezoidal fuzzy numbers. For the validation the results of the pr...

this paper proposes a new mathematical model for the integrated procurement-production-distribution problem of a fuzzy mixed integer linear programming (fmilp) type. considering the uncertainty in real problems, a number of parameters such as demand, capacity, and cost where their values are not available or known precisely, have been considered as trapezoidal fuzzy numbers. to solve fuzzy mixe...

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...

In fuzzy decision problems, the ordering of fuzzy numbers is the basic problem. The fuzzy preference relation is the reasonable representation of preference relations by a fuzzy membership function. This paper studies Nakamura’s and Kołodziejczyk’s preference relations. Eight cases, each representing different levels of overlap between two triangular fuzzy numbers are considered. We analyze the...

envelopment analysis (dea) is a very eective method to evaluate the relative eciency of decision-making units (dmus). dea models divided all dmus in two categories: ecient and inecientdmus, and don't able to discriminant between ecient dmus. on the other hand, the observedvalues of the input and output data in real-life problems are sometimes imprecise or vague, suchas interval data, ...

In this paper, a novel approach for ranking fuzzy numbers based on the angle measure is introduced. Several left and right spreads at each chosen levels of fuzzy numbers is used to determine center of mass points(CMPs) and then, the angels between the CMPs and the horizontal axis is calculated. The total angle is determined by averaging the computed angles and finally, the novel method is compa...

In this paper, a novel approach for ranking fuzzy numbers based on the angle measure is introduced. Several left and right spreads at each chosen levels of fuzzy numbers is used to determine center of mass points(CMPs) and then, the angels between the CMPs and the horizontal axis is calculated. The total angle is determined by averaging the computed angles and finally, the novel method is compa...

Abstract Real-world problems often deal with uncertainties related to imprecision and vagueness, for which fuzzy modeling has provided a successful approach. Ranking numbers is necessary complex task in multiple processes, such as decision making. To facilitate the of ranking numbers, it been introduced an approach construct distances from classical interval because their α-cuts are continuous ...

Ranking of fuzzy numbers play an important role in decision making, optimization, forecasting etc. Fuzzy numbers must be ranked before an action is taken by a decision maker. The main aim of this paper is to propose a new approach for the ranking of generalized fuzzy numbers. The proposed ranking approach is based on distance between positive ideal solution and negative ideal solution. The main...