基于分层禁忌遗传算法的卫星任务调度方案

对地观测卫星在地球观测系统中起着核心作用，任务调度是对地观测卫星满足更多任务需求并获得高观测效率的重要手段。随着用户的激增，大量的任务请求引起卫星资源、时间资源的冲突，导致卫星任务的调度效率低下。为了解决上述问题，通过拆分和聚类2种策略对任务进行预处理，设计了一种基于分层禁忌遗传算法(layered tabu genetic algorithm， LTGA)的卫星任务调度方案。建立了对地观测系统模型，分析了观测任务调度的相关约束；通过分析任务时间窗口冲突情况来确定任务拆分方式，通过计算聚类距离来区分任务分布状态，从而选取合适的观测任务构成预调度任务集合；在上述任务规划的基础上，提出LTGA完成任务的选取和排序，生成观测计划。仿真结果表明，所提出的卫星任务调度方案能够有效提升调度收益、降低调度时间。

Satellite task scheduling scheme based on layered tabu genetic algorithm

Earth observation satellites play a key role in the earth observation system, and task scheduling is an important means for earth observation satellites to meet the needs of more tasks and obtain high observation efficiency. With the rapid increase of users, a large number of task requests cause conflicts of satellite resource and time resource, which leads to the inefficiency of satellite task scheduling. In order to solve the above problems, two strategies of splitting and clustering are used to pre-process tasks, and a satellite task scheduling algorithm based on hierarchical tabu genetic algorithm is designed.Firstly, the earth observation system model is established,and the related constraints of observation task scheduling are analyzed. Then, the way of task splitting is determined by analyzing the conflict of task time window, and the distribution state of tasks is distinguished by clustering distance. Following that, the appropriate observation tasks are selected to form the pre-scheduling task set. Finally, on the basis of the above task planning, LTGA is proposed to complete the task selection and sorting, and generate the observation plan. Simulation results show that the proposed satellite task scheduling scheme can effectively improve scheduling profit and reduce scheduling time.