面 向 预 警 场 景 的 大 规 模 星 座 协 同 调 度 标 准 建 模与 求 解 方 法

Large-scale constellation coordination scheduling is characterized by a large number of remote satellite nodes，large task demands，complex resource utilization constraints，and high requirements for modeling and solving collaborative scheduling between multiple nodes. This paper proposes a top-level framework for phased unified modeling and solving，which includes“task pre-processing，unified modeling，optimization solving，on-orbit instruction generation”. Under the top-level framework，a multi node real-time Collaborative Scheduling Algorithm based on the Improved Contract Network（CSA-ICNP）is proposed for space-based early warning application scenarios，which utilizes fuzzy optimization combined with the local search strategy to improve the overall optimization ability of the algorithm. The correctness and effectiveness of the proposed algorithm are verified by conducting a large number of simulation experiments. Comparison of the method proposed with Random Search algorithm（RS），Greedy Search algorithm（GS），Task Allocation Algorithm based on Conflict Degree（TAACD），Minimum Load First Allocation algorithm（MLFA）and Distributed Satellite Resource Scheduling based on Improved Contract Network Protocol（DSRS-ICNP）shows that each experimental case achieves the optimal objective function value，with an average improvement of 42. 13%，41. 51%，37. 93%，37. 53% and 18. 57%，respectively.