Aviation industry stochastic model based on big data concept

Modern aviation industry is a complex large-scale system that includes designing, testing, production, operation, maintains services, etc. Thus, it seems reasonable to provide information logistical support throughout the life cycle of single processes in this area. On the other hand, it allows building stochastic models to manage aviation industry in real-time mode under uncertainties and risks conditions. It is possible to apply this approach by using Big Data concept. The multi-agent method has been suggested to build the Markov decision process system model of the airline industry life cycle. For discovering the main control action to reduce costs of an airline company, the theoretic-information approach has been applied. The results of the analysis determine the agent action during the decision process to control the amount of freight related to fuel consumption.