Uncertainty analysis for efficient fuel allocation using info-gap theory

Theory decision under uncertainty applies different methods to predict future events, physical measurements, which are already unknown. The paper shows one of the decision-making methods in conditions of severe uncertainty in application to a problem. Some aspects of the robustness and opportuneness functions of Info-Gap Theory are presented and used to evaluate the example of efficient fuel allocation. A general outline of decision analysis is presented, including its orientation and models.