Choquet Aggregation Based Decision Making under Z-information

The concept of decision making under uncertainty is usually associated with information that may be incomplete, not reliable or imprecise, so there are several types of uncertainty. A partial absence of beliefs and fuzziness are some of the aspects of uncertainty. In this paper we consider a somewhat different framework for representing our knowledge. Zadeh suggested a Z-number notion, based on a reliability of the given information. In this study we apply Zinformation to decision making in business problem and suggest the framework for decision making on a base of Z-numbers. The method associates with the construction of a non-additive measure as a lower prevision and uses this capacity in Choquet integral for constructing a utility function. An example of real-world business problem is used to illustrate the proposed approach.