in this paper, we consider portfolio selection problem in which security returns are regarded as fuzzy variables rather than random variables. we first introduce a concept of absolute deviation for fuzzy variables and prove some useful properties, which imply that absolute deviation may be used to measure risk well. then we propose two mean-absolute deviation models by defining risk as abs...

an enterprise resource planning (erp) software is needed for industries and companies that want to develop in future. many of the manufactures and companies have a problem with erp software selection. an inappropriate selection process can affect both the implementation and the performance of the company significantly. although several models are proposed to solve this problem many of them did n...

Three studies were conducted with the goal to articulate and test models for integrating the concept of motivation to reduce uncertainty into the axiomatic structure of uncertainty reduction theory. Multiple models were considered, each model defining motivation to reduce uncertainty in a different way. Motivation to reduce uncertainty was dtfined as a scope condition (Model 2), as tolerance fo...

The book is truly an outstanding work giving a comprehensive exposition of a “generalized information theory” (GIT) having been developed in the early 1990s by Klir. The theory addresses the issue of information-based uncertainty and uncertainty-based information in their various manifestations. The book is organized in ten chapters. Chapter 1 provides the roots, motivations, framework, relevan...

This paper derives an optimal (r; S) policy for uncertain multi-product newsboy problem. Demands for the products are estimated by experts and assumed to be independent uncertain variables. Uncertainty theory, which is a new mathematical tool to deal with human uncertainty, is employed to model demand distributions. A fixed setup cost and a linear ordering cost are incurred if products are orde...

In this article the authors use Actor-Network Theory (ANT) to explore the relationship between uncertainties in co-design processes and the quality of participation. They investigate Latour’s (2005) discussion of uncertainties in social processes concerning the nature of actors, actions, objects, facts/matters of concern and the study of the social. To discuss uncertainties in co-design, and mo...

Reliability analysis and trade-offs between safety cost with insufficient data represent an inevitable problem during the early stage of structural design. In this paper, efficient uncertainty theory-based reliability a design method are proposed under epistemic uncertainty. The factors influencing structure regarded as uncertain variables. Based on this, new metric termed measure is employed t...

Uncertain statistics is a methodology for collecting and interpreting expert’s experimental data by uncertainty theory. And when we collecting the expert’s experimental data, the expert’s data will maybe affected by psychological factors. In this paper, we are giving a rationality test of expert’s experimental data on linear uncertainty distribution of the uncertainty statistics. The testing di...

As a generalization of Dempster-Shafer theory, the theory of D numbers is a new theoretical framework for uncertainty reasoning. Measuring the uncertainty of knowledge or information represented by D numbers is an unsolved issue in that theory. In this paper, inspired by distance based uncertainty measures for Dempster-Shafer theory, a total uncertainty measure for a D number is proposed based ...

Uncertain measure is a set function satisfying normality, duality, subadditivity, and product axioms, and is used to represent the truth value of uncertain event. In order to explore uncertainty theory deeper, this paper constructs a class of inequalities on uncertain measure. These inequalities may give the upper bound or lower bound estimates of the uncertain measure for some uncertain events.