Random fuzzy theory offers an appropriate mechanism to model random fuzzy phenomena, with a random fuzzy variable defined as a function from a credibility space to a collection of random variables. Based on this theory, this paper presents the results of an investigation into the representation of properties of alternating renewal processes that are described by sequences of positive random fuz...

Data Envelopment Analysis (DEA) is a widely used technique for measuring the relative efficiencies of homogenous Decision Making Units (DMUs) with multiple inputs and multiple outputs. These factors may be evaluated in fuzzy or stochastic environment. Hence, the classic structures of DEA model may be changed where in two fold fuzzy stochastic environment. For instances, linearity, feasibility a...

A complex stochastic process is a fundamental connection between two dimensional stochastic processes. Similarly, a complex fuzzy process is proposed and the complex differential and complex Liu integral of complex Liu process are studied in this paper. Especially, some properties of analytic functions of complex Liu process are proved. Finally, complex differential equations are defined.

Fuzzy rule based systems are increasingly being used to deal with time series processes that may lack stochastic stability due to non-stationarity, multiscaling and persistent autocorrelations. Wavelet filtering can be used to deal with such phenomenon. A method for creating a fuzzy-rule base from a time series, where the first difference (returns) of the preprocessed series is used, and high f...

This paper is concerned with the detection and separation of textures or stochastic information within an image. The texture is described mathematical by their stochastic. Because different kinds of stochastic processes generate the textures, they are represented by a system of coupled non-linear stochastic differential equations. If parameters a priori are not known, then their rank and deriva...

A new approach to optimization of processes described by fuzzy rules, in which the functional relationship between the decision variables and the objective function is not completely known, is introduced in this paper. It is based on stochastic algorithms and allows to determine optimal values of state variables and to optimize fuzzy rules (parameters of membership functions). Stochastic algori...

Using Greedy Clustering Method to Solve Capacitated Location-Routing Problem with Fuzzy Demands Abstract In this paper, the capacitated location routing problem with fuzzy demands (CLRP_FD) is considered. In CLRP_FD, facility location problem (FLP) and vehicle routing problem (VRP) are observed simultaneously. Indeed the vehicles and the depots have a predefined capacity to serve the customerst...

A new method of interval computations using fuzzy sets and stochastic processes is proposed. It is concerned with the development of a practical technology that can be used by engineers and researchers to facilitate the process of decision making under uncertainty, in a state of “bounded rationality”. The methodology called Interval Resolution considers a model and interval values specified by ...

Stochastic differential equations (SDEs) have been applied by engineers and economists because it can express the behavior of stochastic processes in compact expressions. In this paper, by using Grunwald-Letnikov fractional derivative, the stochastic differential model is improved. Two numerical examples are presented to show efficiency of the proposed model. A numerical optimization approach b...