Flight Conflict Network Resolution Based on Weighted Cycle Ratio and LDPSO

Aiming at the characterized networking and clustering of flight conflicts in high-density airspace under free-flight mode, this paper proposes a network-based conflict resolution method that integrates complex network theory and an improved particle swarm optimization (PSO) algorithm. First, a tunable Mixed Indicator (MI) is formulated by combining the Weighted Cycle Ratio (WCR) and node strength (NS) to accurately identify critical nodes within the flight conflict network. Subsequently, based on the circle structure, a Circle Complexity (CC) metric is proposed as a network structural indicator. Furthermore, the Analytic Hierarchy Process (AHP) is employed to incorporate network efficiency, the number of conflicting nodes, and robustness into a comprehensive performance evaluation index. On this basis, the Leader–Follower Particle Swarm Optimization (LDPSO) algorithm is applied to collaboratively optimize the discrete codes representing heading, speed, and composite resolution strategies, thereby achieving efficient resolution for multi-aircraft conflicts. Simulation experiments demonstrate that the proposed MI significantly outperforms traditional centrality metrics in identifying critical nodes. The LDPSO algorithm proves superior to comparative algorithms, including the standard PSO, Genetic Algorithm (GA), and Atomic Orbital Optimization (AOO), in terms of conflict resolution rate, convergence speed, and solution quality. It can achieve the rapid disintegration of large-scale conflict networks with relatively low computational cost, providing a feasible solution for real-time conflict resolution in dynamic airspace.