Information Processing in HFMFs Based Risk Evaluation for Virtual Enterprise

Abstract

The method of HFMFs (Hypertrapezoidal Fuzzy Membership Functions) is a new mechanism for designing multidimensional fuzzy sets. HFMFs models the correlation that exists between the variables of the state space. Therefore, it is able to describe the problems of fuzzy situation more exactly. As we known, it needs a great many information to evaluate the risk level for VE using fuzzy synthetic evaluation method. However, there are lots of difficulties to get the needed information for VE. Accordingly, the HFMFs method is introduced to estimate the risk level of VE. Considering not only the relations between different fuzzy sets but also the method of HFMFs is able to describe the problems of fuzzy situation more exactly with less information. Consequently, the HFMFs method is more suitable to the virtual enterprise with little historical experiences than the fuzzy synthetic evaluation method. Simulation has shown that this method is a simple and effective risk evaluation method for VE.