摘要
针对敏捷成像卫星观测任务调度问题,综合考虑卫星最长连续工作时间、任务间卫星姿态调整时间、能量、容量等约束建立了任务调度模型.考虑到密集任务间的相互影响,着重分析了任务间卫星姿态调整时间约束,并给出调姿时间求解方法.提出一种改进蚁群算法对问题进行求解,借鉴蚁群系统(ACS)和最大最小蚂蚁系统(MMAS)的思想设计寻优策略和信息素更新策略.并结合实际约束,引入最早、最晚可观测时间和任务优先级等因素来控制转移概率.实验算例验证了模型和算法的有效性.
The observing task scheduling problem of an agile imaging satellite is studied. The scheduling model is founded considering the complex constraints as the maximal successive working duration, the attitude changing duration between tasks, energy and capacity restriction. Considering the influence among intensive observing tasks, the attitude changing duration is analyzed and a calculating method is given. An improved ant colony algorithm based on ant colony system （ACS） and max-rain ant system （MMAS） is designed to solve the problem. The factors of task priority and bounds of the visible time are introduced into transfer rules. Simulation results show the efficiency of our approach.
出处
《系统工程理论与实践》
EI
CSSCI
CSCD
北大核心
2012年第11期2533-2539,共7页
Systems Engineering-Theory & Practice
基金
国家安全重大基础研究项目(97361361)
关键词
任务调度
建模
蚁群算法
敏捷成像卫星
tasks scheduling
modeling
ant colony algorithm
agile imaging satellite
