In this communication, we study decision influence diagrams using fuzzy sets and fuzzy random variables t,o model problems in which assessing real-valued ~t i l i t~ies , and employing real-valued random variables t o model random magnit,udes, are considered to be too restrictive. We propose conditions allowing us to solve decision influence diagrams when uncertainty magnitudes are formalized b...

This paper presents a multi-product multi-period inventory problem with random replenishment intervals and fuzzy costs under space and shortage level constraints. Since the costs (purchasing, holding and backordering) related to inventory system are often imprecise and the replenishment intervals are random in real life, the proposed model is also fuzzy-random Here, the replenishment intervals ...

Fuzzy random variables possess several interpretations. Historically, they were proposed either as a tool for handling linguistic label information in statistics or to represent uncertainty about classical random variables. Accordingly, there are two different approaches to the definition of the variance of a fuzzy random variable. In the first one, the variance of the fuzzy random variable is ...

The concept of fuzzy random variable has been shown to be as a valuable model for handling fuzzy data in statistical problems. The theory of fuzzy-valued random elements provides a suitable formalization for the management of fuzzy data in the probabilistic setting. A concise overview of fuzzy random variables, focussed on the crucial aspects for data analysis, is presented. © 2006 Elsevier B.V...

in this paper, a model of an optimal control problem with chance constraints is introduced. the parametersof the constraints are fuzzy, random or fuzzy random variables. todefuzzify the constraints, we consider possibility levels.  bychance-constrained programming the chance constraints are converted to crisp constraints which are neither fuzzy nor stochastic and then the resulting classical op...