A linear regression model with imprecise response and p real explanatory variables is analyzed. The imprecision of the response variable is functionally described by means of certain kinds of fuzzy sets, the LR fuzzy sets. The LR fuzzy random variables are introduced to model usual random experiments when the characteristic observed on each result can be described with fuzzy numbers of a partic...

data obtained in association with many real-life random experiments from different fields cannot be perfectly/exactly quantified.hspace{.1cm}often the underlying imprecision can be suitably described in terms of fuzzy numbers/values. for these random experiments, the scale of fuzzy numbers/values enables to capture more variability and subjectivity than that of categorical data, and more accura...

In this paper, we focus on multiobjective integer programming problems with random variable coefficients in objective functions and/or constraints. For such multiobjective problems, after reformulation of them on the basis of an expectation optimization model and a variance minimization model for the chance constrained programming, incorporating fuzzy goals of the decision maker for the objecti...

We shall prove a weak law of large numbers for the uncorrelated (see Definition 3.1) fuzzy random variable sequence with respect to uniform Hausdorff metric $d_H^{\infty}$, which is an extension independent variables.

In this research we concentrate on developing a bifuzzy model for a Single-period inventory problem. The conventional studies have focused on the cases that the demands are probabilistic and follow certain distribution function; or the demands are considered as fuzzy variables; or the demands is expressed by random fuzzy variable. Recently, fuzzy random variables have been applied to some decis...

The data envelopment analytical hierarchy process (DEAHP) is a type of the analytical hierarchy process (AHP), which used the concept of data envelopment analysis (DEA) for generating LW from the judgment matrices and aggregating them to be final weight (FW) in AHP. In general, the judgment scales in AHP is built based on decision maker. It is unrealistic to expect that the decision maker has c...

This paper is on Fuzzy Stochastic Optimisation, an area that is quickly coming to the forefront of mathematical programming under uncertainty. An even stronger motivating factor for the growing interest in this area can be found in the ubiquitous nature of decision problems involving hybrid undeterminacy. More precisely, we consider a range of situations in which random factors and fuzzy inform...

a fully fuzzy linear programming (fflp) formulation for the reservoir operation of amultipurpose reservoir in presented in the ongoing paper. in the real world, water resourcessystems usually have complexities among social, economic, natural resources andenvironmental aspects, which lead to multi-objective problems of significant uncertainties insystem parameters, objectives and in their intera...

in applications there occur different forms of uncertainty. the twomost important types are randomness (stochastic variability) and imprecision(fuzziness). in modelling, the dominating concept to describe uncertainty isusing stochastic models which are based on probability. however, fuzzinessis not stochastic in nature and therefore it is not considered in probabilisticmodels.since many years t...

Random intervals constitute one of the classes of random sets with a greater number of applications. In this paper, we regard them as the imprecise observation of a random variable, and study how to model the information about the probability distribution of this random variable. Two possible models are the probability distributions of the measurable selections and those bounded by the upper pr...