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作 者:杜永浩 邢立宁[1] 姚锋 陈盈果 DU Yong-Hao;XING Li-Ning;YAO Feng;CHEN Ying-Guo(College of Systems Engineering,National University of Defense Technology,Changsha 410073,China;Leiden Institute of Advanced Computer Science,Leiden University,Leiden 2333CA,Netherlands)
机构地区:[1]国防科技大学系统工程学院,中国长沙410073 [2]莱顿大学高级计算研究中心,荷兰莱顿2333CA
出 处:《自动化学报》2021年第12期2715-2741,共27页Acta Automatica Sinica
基 金:国家自然科学基金(61773120,61873328);国家杰出青年科学基金(61525304);高等学校全国优秀博士学位论文作者专项资金(2014-92);国家建设高水平大学公派研究生项目(201903170181);湖南省研究生科研创新项目(CX2018B022)资助。
摘 要:针对航天器任务调度大规模、复杂化的新常态和灵活组网、快速响应的新要求,综述了航天器任务调度模型、算法与通用求解技术的发展现状.首先,基于遥感卫星、中继通信卫星、导航卫星和航天测控等航天器任务,从任务排序模型和时间窗口分配模型两个角度出发,揭示了不同航天器任务调度模型的决策形式和共性特征,阐明提升模型兼容性、适用性的必要性.其次,基于启发式算法、精确求解算法和元启发式算法,探讨了航天器任务调度算法的适用模型与编码特色,指明"算法-模型"解耦、算法深度融合的重要性.在此基础上,介绍了CPLEX、STK/Scheduler、Europa2和"高景一号"任务调度分系统等航天器任务调度通用求解技术的模型、算法与主要功能,说明我国自主研发通用求解技术的必要性和新的应用思路.最后,指出了开发航天器任务调度统一化建模语言、打造算法库与测试集等未来航天器任务调度研究的新方向.To address the large-scale and complicated situations and the flexible networking and fast-response requirements in spacecraft mission scheduling,this paper reviews its developments in models,algorithms and general techniques.Firstly,based on the remote sensing satellite,relay satellite,navigation satellite,and spacecraft tracking missions,the descriptions and commonalities of previous spacecraft scheduling models,including mission-sequencing models and visible time window-allocation models,are analyzed.Also,the necessity of improving model compatibility and applicability is clarified.Secondly,based on heuristic,exact,and metaheuristic algorithms,the applicable models and coding characteristics of those algorithms are discussed,and the importance of algorithm-model decoupling and algorithm hybridization is pointed out.In this regard,the models,algorithms,and main functions of four general techniques for spacecraft mission scheduling,including CPLEX,STK/Scheduler,Europa2,and Super-View-1 scheduling subsystem,are introduced,and the necessity of self-developed general techniques and some new application ideas are explained.Finally,future studies such as developing a unified modeling language and building algorithm libraries and Benchmarks for spacecraft mission scheduling are highlighted.
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