基于改进烟花算法的密集任务成像卫星调度方法

传统卫星调度模型一般比较简单，当问题规模较大、任务比较集中时，往往会出现任务之间相互排斥，任务收益较低等缺点。针对这个问题，提出一种基于改进烟花算法（IFWA）的密集任务成像卫星调度方法。该方法在分析密集任务处理及成像卫星观测特点的基础上，首先对任务进行合成约束分析，然后基于合成任务综合考虑成像卫星可观测时间、任务间姿态调整时间、成像卫星能量和容量等约束因素，建立基于任务合成的多星密集任务调度约束满足问题（CSP）模型，最后改进烟花算法对该模型进行求解，利用精英选择策略在保证种群多样性同时加快了算法的收敛，得到较优的卫星调度方案。仿真结果表明该模型相比没有考虑任务合成因素，收益平均增加30%~35%，改进算法后效率上提升32%~45%，有效保证了调度方案的可行性和有效性。

Satellite scheduling method for intensive tasks based on improved fireworks algorithm

Traditional satellite scheduling models are generally simple, when the problem is large and the tasks are concentrated, the disadvantages of mutual exclusion between tasks and low task revenue often occur. To solve this problem, an intensive task imaging satellite scheduling method based on Improved FireWorks Algorithm (IFWA) was proposed. On the basis of analyzing the characteristics of intensive task processing and imaging satellite observation, synthetic constraint analysis on the tasks was firstly carried out, and then a multi-satellite intensive task scheduling Constraint Satisfaction Problem (CSP) model based on task synthesis was established by comprehensively considering the constraints such as the observable time of the imaging satellite, the attitude adjustment time between tasks, the energy and capacity of the imaging satellite method. Finally, an improved fireworks algorithm was used to solve the model, elitist selection strategy was used to ensure the diversity of population and accelerate the convergence of the algorithm, thus a better satellite scheduling scheme was obtained. The simulation results show that the proposed model increases the average revenue by 30% to 35% and improves the time efficiency by 32% to 45% compared with the scheduling model without consideration of task synthesis factor, which validates its feasibility and effectiveness.