Decision Making with Z-Cross Entropy Preference

Information in decision problems is characterized by partial reliability. To describe such type of information, the concept of Z-numbers was proposed by Zadeh. A basic measure of information uncertainty is entropy, and works on entropy of Z-number are scarce. We propose a new approach to ranking based on cross entropy of Z-numbers to reduce risk of information loss in processing information characterized by high uncertainty.