Interval type-2 fuzzy decision making

This paper concerns itself with decision making under uncertainty and the consideration of risk. Type-1 fuzzy logic by its (essentially) crisp nature is limited in modelling decision making as there is no uncertainty in the membership function. We are interested in the role that interval type-2 fuzzy sets might play in enhancing decision making. Previous work by Bellman and Zadeh considered decision making to be based on goals and constraints. They deployed type-1 fuzzy sets. This paper extends this notion to interval type-2 fuzzy sets and presents a new approach to using interval type-2 fuzzy sets in a decision making situation taking into account the risk associated with the decision making. The explicit consideration of risk levels increases the solution space of the decision process and thus enables better decisions. We explain the new approach and provide two examples to show how this new approach works. •Interval type-2 decision making extends Bellman and Zadeh's type-1 decision making.•The acceptable level of risk can be explicitly specified.•Considering risk levels increases the solution space of the decision process.•The larger solution space of the type-2 approach enables better decisions.•In a traffic application, the decision quality could be improved by 5.3–8.1%.