Several authors have proposed different methods to find the solution of fully fuzzy linear programming (FFLP) problems. But all the existing methods are based on the assumption that all the fuzzy coefficients and the fuzzy variables are non-negative fuzzy numbers. in this paper a new method is proposed to solve an FFLP problems with arbitrary fuzzy coefficients and arbitrary fuzzy variables, that is, there is no restriction on the elements that have been used in the FFLP problems. By using the radius of gyration function (ROG) we show that fuzzy solution obtained of solving FFLP problems, is exact fuzzy optimal solution of FFLP problems. The introduce method are very easy to understand and to apply for fully fuzzy linear systems occurring in real life ‎situation.‎ تفاصيل المقالة

تفاصيل المقالة

تفاصيل المقالة

‎This paper deals with one problem that needs to be addressed in the emerging field known under the name computing with perceptions‎. ‎It is the problem of describing‎, ‎approximately‎, ‎a given fuzzy set in natural‎ ‎language‎. ‎This problem has lately been referred to as the problem of retranslation‎. ‎An approaches to ‎dealing with the retranslation problem is discussed in the paper‎, ‎that is based on a pre-defined set of ‎linguistic terms and the associated fuzzy sets‎. ‎The retranslation problem is discussed in ‎terms of two criteria validity and informativeness‎. تفاصيل المقالة

Here we consider approaches to the ranking of fuzzy numbers based upon the idea of associating with a fuzzy number a scalar value, its signal/noise ratios, where the signal and the noise are defined as the middle-point and the spread of each $\gamma$-cut of a fuzzy number, respectively. We use the value of a as the weight of the signal/noise ratio of each $\gamma$-cut of a fuzzy number to calculate the ranking index of each fuzzy number. The proposed method can rank any kinds of fuzzy numbers with different kinds of membership functions.‎ تفاصيل المقالة

‎A new method for the defuzzification of fuzzy numbers is developed in this paper. It is well-known, defuzzification methods allow us to find aggregative crisp numbers or crisp set for fuzzy numbers. But different fuzzy numbers are often converted into one crisp number. In this case the loss of essential information is possible. It may result in inadequate final conclusions, for example, expert estimation problems, prediction problems, etc. Accordingly, the necessity to develop a method for the defuzzification of fuzzy numbers, allowing us to save their informative properties has arisen. The purpose of this paper is to develop such a method. The method allows us to find aggregative intervals for fuzzy numbers. These intervals are called the Regular weighted intervals. We start with the definition of regular weighted points for fuzzy numbers. The regular weighted interval for fuzzy number is defined as the set of regular weighted points of all unimodal numbers, that belong to this number. Some propositions and examples about regular weighted point and regular weighted intervals properties are ‎offered.‎ تفاصيل المقالة