Random utility models have been widely used in many diverse fields. Considering utility as a random variable opened many new analytical doors to researchers in explaining behavioral phenomena. Introducing and incorporating the random error term into the utility function had several reasons, including accounting for unobserved variables. This paper incorporates fuzziness into random utility mode...

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...

In this paper, we first consider a Bayesian frame­ work and model the "utility function" in terms of fuzzy random variables. On the basis of this model, we define the "prior (fuzzy) expected util­ ity" associated with each action, and the cor­ responding "posterior (fuzzy) expected utility given sample information from a random exper­ iment". The aim of this paper is to analyze how sample infor...

Nowadays high fuzzy utility based pattern mining is an emerging topic in data mining. It refers to discover all patterns having a high utility meeting a user-specified minimum high utility threshold. It comprises extracting patterns which are highly accessed in mobile web service sequences. Different from the traditional fuzzy approach, high fuzzy utility mining considers not only counts of mob...

This paper establishes a theory of decision making under uncertainty with fuzzy utilities. The extension of expected utility and stochastic dominance to the comparison of sets of random variables plays a crucial role. Their properties as fuzzy rankings are studied, and their definitions are further generalized to the comparison of fuzzy random variables. Also, a connection between expected util...

this paper studies housing choice under fuzzy circumstances. in this article, fuzzy distance method is employed for selection process. methodology of housing choice with fuzzy distance approach is based on the minimizing fuzzy distance of features from desired amount under fuzzy condition. meanwhile, in the discrete choice models, housing choice is based on utility maximizing of available optio...

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...

The random utility model is known to be unidentified, but there are times when the admits a unique representation. We offer two characterizations for existence of Our first characterization puts conditions on graphical representation data set. Non-uniqueness arises multiple inflows can assigned outflows this graph. second provides direct test uniqueness given also show that support identified i...

We generalize the stochastic revealed preference methodology of McFadden and Richter (1990) for finite choice sets to settings with limited consideration. Our approach is nonparametric requires partial set variation. impose a monotonicity condition on attention first proposed by Cattaneo et al. (2020) stability marginal distribution preferences. framework amenable statistical testing. These new...

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...