Intuitionistic fuzzy multiple attribute decision making and its application for network selection

In heterogeneous wireless networks, an important task for mobile terminals is network selection. A main challenge of network selection is to represent the uncertainty. Concerning this challenge, we investigate intuitionistic fuzzy multi-attribute decision making (IFMADM) and discuss its application in network selection. Objectively determining attribute weights and aggregating intuitionistic fuzzy information belong to two key points to establish IFMADM models. This paper proposes an IFMADM method based on relative entropy and Dempster-Shafer (D-S) theory to solve afore-mentioned two key problems of IFMADM. The proposed method utilizes relative entropy to solve the problem of determining objective attribute weights for the MADM problems with completely unknown attribute information. Moreover, an aggregation approach based on D-S theory is proposed for combining with intuitionistic fuzzy information. On the basis of above work, an IFMADM model is established. The simulation shows the validity and feasibility of the proposed decision making method.