Problem statement: The task of real time cargo traffic scheduling for the International Space Station (ISS) is considered. The problem of strategic and tactical scheduling of the flights, delivery, return, disposal and allocation of ISS cargo traffic, including more than 3500 entities, is very complex and time-consuming. In order to solve this problem it is important to take into consideration numerous factors, constraints and preferences, such as changing fuel, water and supplies demand, ballistics and solar activity, particular types of spaceships and docking modules. Changes in dates of launch, landing, docking and undocking, crew size and other parameters affect the flight program and cargo traffic. These changes cause dynamic rescheduling in the chain of changes of the interconnected parameters, which would be specified, recalculated and coordinated. The problem is formalized as a dynamical balance of interests (consensus) between the orders and resources. Methods: The method of real-time adaptive cargo traffic rescheduling is proposed. The method is based on a multi-agent technology for identification and solving of conflicts by negotiations of agents. ISS cargo traffic scheduling method develops the suggested method of conjugate interactions in the Demand-Resource Networks (DRN) by using cargo priorities. The advantages of the suggested solution for the adaptive events processing without stopping and restarting of the system are shown. Benefits of the method include high flexibility and efficiency for the event-driven adaptation of the cargo schedules in real time. Results: The developed method was implemented in the multi-agent system for ISS cargo scheduling with the use of a multi-agent platform for real time scheduling. Practical relevance: The developed system is based on the multi-agent technologies and is now in commercial operation. It is applied in the cargo traffic scheduling for the Russian Segment of ISS. The system ensures such advantages as ISS cargo traffic scheduling similar to the schedules created by experienced operators; flexible and quick reaction to the events which cause cargo traffic rescheduling; double or triple reduction of the manual labor and increase of the decision-making efficiency; real-time monitoring and control of the schedule implementation.