Survey on Models, Algorithms and General Techniques for Spacecraft Mission Scheduling
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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.Abstract: 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 SuperView-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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Key words:
- Spacecraft /
- mission scheduling /
- scheduling model /
- scheduling algorithm /
- general technique
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图 1 遥感卫星任务排序模型示例
Fig. 1 Illustrations of mission-sequencing models for remote sensing satellites
图 2 遥感卫星VTW分配模型示例
Fig. 2 Illustrations of VTW-allocation models for remote sensing satellites
图 3 敏捷遥感卫星任务离散VTW分配模型示例
Fig. 3 An illustration of the discrete VTW-allocation model for agile remote sensing satellites
图 4 中继通信卫星任务调度问题与遥感卫星任务调度问题的类比
Fig. 4 A comparison between the mission scheduling of relay satellites and remote sensing satellites
图 6 航天器任务调度模型主要参数关系的一种类图表示(以遥感卫星为例)
Fig. 6 A class diagram of the relationships among the parameters in spacecraft mission scheduling (exampled by remote sensing satellites)
图 7 遗传算法求解航天器任务调度问题编码示例
Fig. 7 Illustrations of the GA encoding for spacecraft mission scheduling
表 1 航天器任务调度模型研究现状总结
Table 1 A summary of the studied models for spacecraft mission scheduling
模型类型 模型子类 编码过程 解码过程 模型优缺点 常见约束 极少考虑的业务约束 面向资源
的任务排
序模型VRP模型 决策变量表示资源执行任务的顺序 规则与约束决定开始时间, 解码后为可行解 1) 表示了任务顺序, 便于检查任务顺序和转换时间约束
2) 在“顺序回放”工作机制下同时决策成像与数传序列
3) 不便于描述长VTW的任务调度问题与复杂约束
4) “最优序列”不一定等于“最优结果”, 约束越复杂, 解码过程越可能丢失优质解, 解码的时间成本也越高1) 任务执行唯一性约束
2) 任务可见性约束(即时、空、频域VTW)
3) 任务顺序约束(如条带拼接、立体成像、顺序回放等)
4) 任务工作模式约束(如遥感卫星记录、回放、实传模式与录放比约束)
5) 资源能力约束(如卫星电池、固存容量、任务次数; 测控与数传站负载、工作频率、时长约束等)
6) 资源转换时间约束
7) 资源可抢占性与非抢占性约束(如测控任务相控阵等待期可执行其他任务)1) 非线性、函数化、过程依赖的资源能力、转换时间约束(如遥感卫星单轨成像时限与该轨侧摆次数、最小摆角、是否实传等相关)
2) 区分连续、非连续任务的资源能力、转换时间约束(如“高景一号”单轨连续成像次数、时间限制)
3) 区分阳照条件的资源能力、转换时间约束(如地影区中继卫星工作时限)
4) 区分待机、工作等的资源能力、转换时间约束(如载荷开关机、执行任务时限)
5) 单载荷资源模式切换约束(如“北斗”地面站时间同步与数据传输模式的切换)
6) 多载荷资源模式切换约束(如“资源一号”可见光与高光谱模式的切换)
7) 遥感卫星基于“整块擦除”的固存管理约束图论模型 JSP模型 优先级排序模型 通过决策变量表示任务分配资源的顺序 面向任务
的VTW分
配模型基于规则的
分配模型通过0−1变量表示任务的VTW 基于规则与
约束决定开
始时间, 解码
后为可行解1) 直接表达了任务VTW和开始时间, 反映了任务顺序
2) 不限于“顺序回放”, 可分别调度成像与数传序列
3) 能够描述长VTW的任务调度问题与复杂约束
4) 基于规则的分配模型解空间较小, 但也存在解码过程
5) 多重决策和离散VTW分配模型更加完备, 提升了解的多样性, 但解空间较大多重决策的
分配模型通过0−1变量和整数变量分别表示VTW与开始时间 不检查约束, 解码后可能
为不可行解离散化VTW
分配模型通过0−1变量直接表示离散VTW及开始时间 
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表 2 航天器任务调度研究中常用算法总结
Table 2 A summary of commonly used algorithms for spacecraft mission scheduling
算法类型 算法子类 常用编码模型 算法优点 算法不足 启发式算法 优先级排序算法 任务排序模型 1) 结构简单、运算速度快
2) 符合人的主观认识, 有经验支撑
3) 有助于缩减问题解空间, 在与其他算法组合使用过程中提升求解效率1) 与问题特征和调度模型紧耦合, 通用化程度不高
2) 求解效果欠佳, 常用于辅助决策, 很少直接用于调度方案的生成冲突消解算法 以任务排序模型为主 任务分配算法 以VTW分配模型为主 精确算法 分支定界算法 任务排序或VTW分配模型 1) 可以求得最优解, 在不确定性条件下也能保证解的最优性
2) 算法思想对其他算法有指导意义, 与其他算法有良好的组合应用前景1) 只适用于小规模、简单约束问题, 求解大规模、复杂约束问题能力有限
2) 通常需要较大程度的问题简化动态规划算法 元启发式算法 演化算法 遗传算法 任务排序或VTW分配模型 1) 具有隐并行性和多样的解表示能力
2) 具有出色的全局寻优能力
3) 与其他算法混合的兼容性好
4) 任务排序模型的编码形式简洁、操作简单1) 局部搜索能力有限
2) 任务排序模型的编码方式可能丢失优质解
3) VTW分配模型的编码方式复杂且冗长, 可能影响优化效率蚁群算法 以任务排序模型为主 粒子群算法 以VTW分配模型为主 局部搜索 禁忌搜索算法 任务排序或VTW分配模型 1) 原理简单、易于实现、适用性好
2) 具有出色的局部搜索能力
3) 具有一定的局部最优逃逸能力1) 全局搜索能力有限, 易陷入局部最优
2) 依赖于邻域结构的设计模拟退火算法 以VTW分配模型为主 其他算法 模因算法 任务排序或VTW分配模型 对局部搜索和演化算法取长补短 依赖于框架设计, 可能降低迭代效率 机器学习决策算法 以任务排序模型为主 简单、快速并且自适应、自学习 “来一个决策一个”, 缺乏全局优化性
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表 3 用于航天任务调度的通用求解器总结
Table 3 A summary of the general techniques for spacecraft mission scheduling
通用求解器 常用调度模型 求解算法 求解器优点 求解器不足 CPLEX 线性规划模型表示的任务排序模型或VTW分配模型 分支定界算法等精确求解算法 1) 语言简洁, 兼容性好
2) 内置算法丰富, 降低算法设计难度, 同时开放了算法设计与改进接口
3) 可以求得最优解, 在不确定性条件下也能保证解的最优性
4) 用户基础大, 版本持续更新1) 很难描述非线性约束或收益, 复杂约束线性化难度大
2) 很难求解大规模任务调度问题
3) 算法改进对线性规划理论基础要求高
4) 缺乏航天领域特色STK/Scheduler 任务排序模型 任务排序算法, 冲突消解算法 1) 与STK兼容, 建模简单
2) 语言简洁, 兼容性好
3) STK/Scheduler Online具有远程服务功能1) 封装程度较高, 难以描述复杂约束, 二次开发难度大
2) 缺乏动态调整功能
3) 算法优化能力有限, 版本无持续更新VTW分配模型 任务分配算法, 冲突消解算法 Europa2 通过标记、事务、对象、类、时间线、规划解描述一个规划模型 约束传播等约束规划算法 1) 面向状态变量和动作序列, 求解过程直观
2) 约束传播算法有助于动态调度机制的设计1) 缺乏收益函数和调度优化机制
2) 只适用于小规模(单星单轨)任务调度, 版本无持续更新“高景一号”任务调度分系统 任务排序模型 基于最早开始原则的任务排序算法 1) 模型与算法简洁
2) 可以考虑全部复杂约束1) 调度质量有待提高
2) 动态调整以人工为主, 结果无法实时反馈
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