this paper presents a fuzzy decision-making approach to deal with a clustering supplier problem in a supply chain system. during recent years, determining suitable suppliers in the supply chain has become a key strategic consideration. however, the nature of these decisions is usually complex and unstructured. in general, many quantitative and qualitative factors, such as quality, price, and fl...

In this paper, an approach is introduced which permits a model-free identification and prediction of time-dependent structural behavior. The numerical approach is based on recurrent neural networks for uncertain data. Time-dependent results obtained from measurements or numerical analysis are used to identify the uncertain long-term behavior of engineering structures. Thereby, the uncertainty o...

The fuzzy measure can highlight important information in analyzing component features, patterns, and trends. However, fuzzy densities and interaction effects are usually unknown or uncertain for implications thus making the fuzzy measure limited in applications. This research proposes an extended fuzzy measure to derive the conditional fuzzy densities from dominance-based rough set approach (DR...

Classical deterministic inventory models consider the demand rate to be either constant or time-dependent but independent from the stock status. However, for a certain type of inventory, the demand rate may be in-fluenced by the stock level. Also in many real-life problems, some products such as fruits, vegetables, phar-maceuticals and volatile liquids continuously deteriorate to evaporation, o...

classical deterministic inventory models consider the demand rate to be either constant or time-dependent but independent from the stock status. however, for a certain type of inventory, the demand rate may be in-fluenced by the stock level. also in many real-life problems, some products such as fruits, vegetables, phar-maceuticals and volatile liquids continuously deteriorate to evaporation, o...

in the course of the present study, the results of parametric approach are compared with those obtained through fuzzy approach using ahp as well as multivariate regression methods for comparisons and investigating the efficiency of the fuzzy method as applied in land suitability assessments. the correlation coefficients between land index and observed yield in the study area through fuzzy appro...

this article presents a fuzzy robust mixed - sensitivity gain - scheduled h controller based on the loop -shaping methodology for a class of mimo uncertain nonlinear time - varying systems. in order to design this controller, the nonlinear parameter - dependent plant is first modeled as a set of linear subsystems by takagi and sugeno’s (t - s) fuzzy approach. both loop - shaping methodology and...

In this paper, we introduce a new mathematical programming approach to estimate the parameters of fuzzy linear regression with crisp/fuzzy input and fuzzy output. The advantage of this approach is, both of dependent and independent variables are influenced on the objective function. Therefore, this model rectifies some problems about outliers. Also, in this paper we use possibility function in ...

In this paper, a new approach is presented to fit arobust fuzzy regression model based on some fuzzy quantities. Inthis approach, we first introduce a new distance between two fuzzynumbers using the kernel function, and then, based on the leastsquares method, the parameters of fuzzy regression model isestimated. The proposed approach has a suitable performance to<b...