摘要 : The Decision making has been a major research topic in the computing literature for so long due to its vast significance in many real-world applications. Traditional fuzzy decision making (FDM) approaches have limitations due to t... 展开 The Decision making has been a major research topic in the computing literature for so long due to its vast significance in many real-world applications. Traditional fuzzy decision making (FDM) approaches have limitations due to the inability of the type-1 fuzzy sets (T1 FSs) in modeling higher order uncertainties. Since, the membership function (MF) of an interval type-2 fuzzy set (IT2 FS) is also fuzzy, as superior to T1 FSs, researchers considered IT2 FSs to model higher level of uncertainties in FDM and proposed a number of IT2 FDM methods. However, unlike IT2 FSs, general type-2 fuzzy sets (GT2 FSs) do not consider equal secondary membership values for all its primary membership functions. Hence, GT2 FSs offer more suitability in modelling uncertainties that exist in real-world scenarios. Thus, this paper proposes a more efficient decision making method called the "GT2 Fuzzy Decision Making (GT2 FDM)", which considers GT2 FSs to model the fuzzy goals and fuzzy constraints in a problem. The working of the proposed approach is demonstrated using an example of room temperature selection. Then we have applied it to the problem of convenient travel time selection using a real-time traffic data set. It is observed that the proposed GT2 FDM approach offers more flexibility to the decision makers in choosing an optimal solution from a much wider solution space and hence is found to be more efficient than the IT2 FDM and classical FDM approaches. 收起