In classical fuzzy sets, for an element of a fuzzy set only one membership value is assigned which is between 0 and 1. Torra (Int. J. Intell. Syst. 25:529–539, [1]) introduced the hesitant fuzzy sets (HFSs) where more than one membership function value can be assigned to an element. This issue is very useful for decision makers in order to determine the membership values. HFSs can be used when the experts face hesitancy for making decisions. As an example assume that an expert considers the alternatives “average” and “good” for assessing the quality on an automobile where each of these alternatives have several membership function between 0.6 and 0.8.