Conflict resolution(CR)plays a crucial role in safe air trafc 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 diferent 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 efectively and efciently 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. Conflict resolution (CR) plays a crucial role in safe air trafc 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 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. sub-groups are adjusted dynamically as new conflicts appear after each iteration. Secondarily, a fast genetic algorithm (GA) is used by each sub-group to optimize the paths of the aircraft , the aircraft’s optimal paths are obtained through cooperation among diferent sub-groups based on cooperative co-evolutionary (CC). An experimental study on two illustrative scenarios is conduc ted to compare the CCDG method with some other existing approaches and it is shown that CCDG which can get the optimal solution efectively and efciently 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.