The Task Scheduling Model and Algorithm for Imaging Satellites with Optimizing Satellite Service Life
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摘要: 基于组网卫星协同工作规划可提高复杂任务处理的基础上,本文探索降低规划风险,提高卫星服务寿命的卫星任务规划方法.从提高卫星服务寿命角度,建立用于描述资源使用期望的目标规划模型;建立卫星任务规划模型,在任务方案与资源使用中考虑了规划风险要素,并将资源使用目标模型引入到任务规划模型中,以期在规划中同时优化卫星服务寿命要素;基于邻域贪心扩展改善遗传禁忌求解算法,并运用分布并行技术提高工程实用性;利用STK提供基础仿真数据,对模型与算法进行了验证.Abstract: Complicated collaborative tasks can be performed by networking satellites, and the resource cost and the scheduling risk can also be optimized by building an effective task-scheduling model. This paper describe three respects of the work. First, the goal programming model is established to describe the resource usage expectations, made by satellite experts in view of satellite service life. Second, a task scheduling model is established to optimize the task gains, the resource cost and the scheduling risk. Third, a gene algorithm and a tabu algorithm are combined to solve the model, since the scheduling problem is an NP-hard problem; furthermore, the solving algorithm is extended by neighbor greedy search to improve the convergence rate and robustness of the algorithm. Finally, a distributed parallel method is adopted to improve the effectiveness.
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