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In air-based information network of the Space-Air-Ground Integrated Network, it is critical to select an efficient communication link for each communication. However, some communication may not have fixed rules. In this article, we build a model of the air-based information network, and use the dynamic programming to select the most efficient communication link by minimizing the energy consumption in the communication model. In the communication model, energy consumption is associated with the distance between aircrafts and the relative velocity of the aircrafts. There is a given example used to describe the communication subnetworks of aircrafts in the air-based information network, and how each subnetwork containing multiple aircrafts communicates efficiently with the optimization by using the presented algorithms. The experiments show that the presented algorithms can effectively reduce the total cost while satisfying timing constraints with guaranteed confidence probabilities. For example, there has been an achievement that an average reduction of 9.9 % per 20 time units in the 100-subnetwork model satisfying timing constraints based on the presented algorithm.

Conflict resolution (CR) plays a crucial role in safe air traffic management (ATM). In this paper, we propose a new hybrid distributed-centralized tactical CR approach based on cooperative co-evolutionary named the CCDG (cooperative co-evolutionary with dynamic grouping) strategy to overcome the drawbacks of the current two types of approaches, the totally centralized approach and distributed approach. Firstly, aircraft are divided into several sub-groups based on their interdependence. Besides, a dynamic grouping strategy is proposed to group the aircraft to better deal with the tight coupling among them. The sub-groups are adjusted dynamically as new conflicts appear after each iteration. Secondly, a fast genetic algorithm (GA) is used by each sub-group to optimize the paths of the aircraft simultaneously. Thirdly, the aircraft’s optimal paths are obtained through cooperation among different sub-groups based on cooperative co-evolutionary (CC). An experimental study on two illustrative scenarios is conducted to compare the CCDG method with some other existing approaches and it is shown that CCDG which can get the optimal solution effectively and efficiently in near real time, outperforms most of the existing approaches including Stratway, the fast GA, a general evolutionary path planner, as well as three well-known cooperative co-evolution algorithms.