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面向成像卫星组网的群任务规划方法研究
引用本文:姜维,庞秀丽. 面向成像卫星组网的群任务规划方法研究[J]. 系统工程理论与实践, 2014, 34(8): 2154-2162. DOI: 10.12011/1000-6788(2014)8-2154
作者姓名:姜维  庞秀丽
作者单位:哈尔滨工业大学 管理学院, 哈尔滨 150001
基金项目:国家自然科学基金(71271066,71202168);中央高校基本科研业务费专项资金(HIT.NSRIF.2010083);中国博士后基金(20090450973);博士后科研启动基金(LBH-Q11132)
摘    要:本文基于提高用户任务需求的处理能力,探索可共享卫星资源组网卫星协同的群规划方法.研究中不仅考虑了一些部门存在特有的任务规划需求,还考虑到一些重要部门有卫星资源或者经申请有允许规划的卫星资源. 分析了群规划的模式需求及提出群规划框架;针对分层规划与可共享的资源服务,建立群规划多目标优化模型;针对任务规划这一高维离散组合优化问题,借鉴蚁群算法的快速收敛和遗传算法的强知识表示能力,阐述组合高低阶知识表示的改进遗传求解算法. 仿真实验验证了本文规划模型与求解算法的有效性.

关 键 词:卫星任务规划  群规划模型  求解算法  遗传算法  
收稿时间:2012-10-31

The group scheduling method for the tasks of imaging satellite network
JIANG Wei,PANG Xiu-li. The group scheduling method for the tasks of imaging satellite network[J]. Systems Engineering —Theory & Practice, 2014, 34(8): 2154-2162. DOI: 10.12011/1000-6788(2014)8-2154
Authors:JIANG Wei  PANG Xiu-li
Affiliation:School of Management, Harbin Institute of Technology, Harbin 150001, China
Abstract:The collaborative work of the multi imaging satellites can deal with the complicated tasks of users. On the one hand, some departments have the special task execution characteristics and they want to make task scheduling alone. On the other hand, some important departments or have their own resources, or have their own planning resources after applying and approval. This paper discusses the group scheduling of the shared satellite resources: Firstly, analyses the requirement of group scheduling and exhibit the framework of group scheduling; Secondly, building the model of group scheduling to perform the task scheduling of shared satellite resources; Thirdly, inspiring by the good convergence of ant algorithm and the good description ability of gene algorithm, this paper presents the improved gene algorithm by combining high order knowledge and low order knowledge, to solve the model. Finally, simulation experiments validate the effectiveness of task scheduling model and algorithm.
Keywords:satellite task scheduling  group scheduling model  scheduling algorithm  gene algorithm  
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