Advances in carrier-based aircraft deck operation scheduling
LIU Ao1,2, LIU Ke3
1. School of Management, Wuhan University of Science and Technology, Wuhan 430081, China; 2. Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan 430065, China; 3. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
Abstract：In recent years, a novel application domain of scheduling, namely carrier-based aircraft deck operation scheduling is emerged. As an unexplored domain of scheduling, carrier-based aircraft deck operation scheduling has attracted more and more attention from both academic and industrial experts in the filed of scheduling, control theory and operations research et al. In this paper, a survey of carrier-based aircraft deck operation scheduling problem is presented both at home and abroad. Firstly, the carrier-based aircraft deck operation scheduling problem is formulated as a fundamental mixed integer programming mathematical model; secondly, a comprehensive review at abroad is given, which mainly focuses on United States; thirdly, four related topics of carrier-based aircraft deck operation scheduling at home are classified, including system simulation, system design, system optimization, and route planning. Finally, we conclude this survey with future trends and further research directions. This study aims to promote theoretical research and engineering applications of carrier-based aircraft deck operation scheduling problem at home.
[1] Li N, Weuve C. China's aircraft carrier ambitions: An update[R]. US Navy: Naval War College Newport Research Institute, 2010. [2] U.S. Naval Air Systems Command. CVN flight-hanger deck NATOPS manual[R]. Washington: NACYAIR 00-80T-120, 2008. [3] Jewell A, Wigge M A, Gagnon C M, et al. USS Nimitz and carrier airwing nine surge demonstration[R]. US Navy: Center for Naval Analyses, 1998. [4] Jewell A. Sortie generation capacity of embarked airwings[R]. US Navy: Center for Naval Analyses, 1998. [5] Pinedo M L. Scheduling: Theory, algorithms, and systems[M]. New York: Springer Science & Business Media, 2012. [6] Ryan J C, Cummings M L, Roy N, et al. Designing an interactive local and global decision support system for aircraft carrier deck scheduling[C]//Proceedings of AIAA Information Technology, 2011: 1-12. [7] Michini B, How J P. A human-interactive course of action planner for aircraft carrier deck operations[J]. AIAA, 2011: 1-11. [8] 司维超, 韩维, 史玮韦. 基于PSO算法的舰载机舰面布放调度方法研究[J]. 航空学报, 2012, 33(11): 2048-2056.Si W C, Han W, Shi W W. Research on deck-disposed scheduling method of carrier planes based on PSO algorithm[J]. Acta Aeronautica et Astronautica Sinica, 2012, 33(11): 2048-2056. [9] 司维超, 韩维, 史玮韦. 基于HPSO算法和GA的舰载机甲板布放方法比较[J]. 系统工程与电子技术, 2013, 35(2): 338-344.Si W C, Han W, Shi W W. Comparison of deck-disposed methods for shipboard aircraft based on HPSO and GA[J]. Journal of Systems Engineering and Electronics, 2013, 35(2): 338-344. [10] 司维超, 韩维. 基于多种群协作混沌智能算法的舰载机出动调度[J]. 计算机应用研究, 2013, 30(2): 454-457.Si W C, Han W. Takeoff scheduling of carrier plane based on multi-colonies cooperation and CLS intelligence algorithm[J]. Application Research of Computers, 2013, 30(2): 454-457. [11] 韩维, 司维超, 丁大春, 等. 基于聚类PSO算法的舰载机舰面多路径动态规划[J]. 北京航空航天大学学报, 2013, 39(5): 610-614.Han W, Si W C, Ding D C, et al. Multi-routes dynamic planning on deck of carrier plane based on clustering PSO[J]. Journal of Beijing University of Aeronautics and Aerospace, 2013, 39(5): 610-614. [12] 张洪涛, 崔珊珊, 刘广, 等. 机群保障资源配置建模与优化研究[J]. 系统工程理论与实践, 2015, 35(4): 1019-1026.Zhang H T, Cui S S, Liu G, et al. Resource scheduling for air fleet operations[J]. Systems Engineering-Theory & Practice, 2015, 35(4): 1019-1026. [13] Navy Air. Taking the Ouija board out of flight operations[OL]. http: //www.strategypage.com/htmw, 2011-08-12. [14] Johnston J S. A feasibility study of a persistent monitoring system for the flight deck of US Navy aircraft carriers[R]. Air Force Institute of Tech Wright-Paterson: Graduate School of Engineering and Management, 2009. [15] Navy Training System Plans. Navy training system plan for the aviation data management and control system (N78-NTSP-A-50-0009/A)[R]. USA: Navy Air Command, 2002. [16] 石剑琛. 美国海军航母作战系统发展及展望[J]. 舰船科学技术, 2012, 34(4): 133-135.Shi J C. The development and prospect of US navy carrier combat system[J]. Ship Science and Technology, 2012, 34(4): 133-135. [17] Johnston J S. A feasibility study of a persistent monitoring system for the flight deck of US navy aircraft carriers[R]. Air Force Institute of Tech Wright-Paterson: Graduate School of Engineering and Management, 2009. [18] Johnston J S, Swenson E D. Feasibility study of global-positioning-system-based aircraft-carrier flight-deck persistent monitoring system[J]. Journal of Aircraft, 2010, 47(5): 1624-1635. [19] Navy Stripes. Old-school Ouija board being phased out on navy carriers[OL]. http: //www.stripes.com/news/navy/old-school-ouija-board-being-phased-out-on-navy-carriers-1.151711, 2011-08-10. [20] Rainwater C W. An exploratory study of an automated carrier aircraft deck operations control system[R]. US Navy: Naval Air Engineering Center, 1966. [21] Rainwater C W. CADOCS subsystems: Parameter definition[R]. US Navy: Naval Air Engineering Center, 1967. [22] Rainwater C W. CADOCS subsystem requirements studies[R]. US Navy: Naval Air Engineering Center, 1968. [23] Giardina T J. An interactive graphics approach to the flight deck handling problem[D]. USA: Naval Postgraduate School, 1974. [24] Johnson A K. A simulation of a computer graphics-aided aircraft handling system[D]. USA: Naval Postgraduate School, 1975. [25] John C B. An expert system for aviation squadron flight scheduling[D]. USA: Naval Postgraduate School, 1991. [26] Thate T, Michels A. Requirements for digitized aircraft spotting board for use on US navy aircraft carriers[D]. USA: Naval Postgraduate School, 2002. [27] Ruff H A, Narayanan S, Draper M H. Human interaction with levels of automation and decision-aid fidelity in the supervisory control of multiple simulated unmanned air vehicles[J]. Presence: Teleoperators and Virtual Environments, 2002, 11(4): 335-351. [28] Dastidar R G, Frazzoli E. A queueing network based approach to distributed aircraft carrier deck scheduling[J]. AIAA, 2011: 1514-1164. [29] Ryan J C, Banerjee A G, Cummings M L, et al. Comparing the performance of expert user heuristics and an integer linear program in aircraft carrier deck operations[J]. IEEE Transactions on Cybernetics, 2014, 44(6): 761-773. [30] Ryan J C. Investigating possible effects of UAVs on aircraft carrier deck operations[R]. Cambridge: Humans and Automation Laboratory, MIT, 2011. [31] Ryan J C. Assessing the performance of human-automation collaborative planning systems[D]. USA: Massachusetts Institute of Technology, 2011. [32] Sastry V V, Steel J, Trott E A. A virtual environment for naval flight deck operations training[R]. RTO HFM Workshop, 2000: 1-6. [33] Coutard L, Chaumette F, Pflimlin J M. Automatic landing on aircraft carrier by visual servoing[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2011: 2843-2848. [34] Sebok A, Wickens C, Sarter N, et al. The automation design advisor tool (ADAT): Development and validation of a model-based tool to support flight deck automation design for nextgen operations[J]. Human Factors and Ergonomics in Manufacturing & Service Industries, 2012, 22(5): 378-394. [35] 郭元江, 李会杰, 申功璋. 复杂环境下舰载机弹射起飞环境因素建模分析[J]. 北京航空航天大学学报, 2011, 7: 877-881.Guo Y J, Li H J, Shen G Z. Modeling and analyze of the environmental factors of carrier-based aircraft catapult launch in complex environment[J]. Journal of Beijing University of Aeronautics and Astronautics, 2011, 7: 877-881. [36] 程刚, 倪何, 孙丰瑞. 舰载蒸汽弹射系统建模与仿真研究[J]. 武汉理工大学学报(交通科学与工程版), 2010, 34(2): 301-305.Cheng G, Ni H, Sun F R. Modeling and simulation research on naval steam-power aircraft launch system[J]. Journal of Wuhan University of Technology (Transportation Science & Engineering), 2010, 34(2): 301-305. [37] 朱熠. 舰载机起飞控制与仿真技术研究[D]. 南京: 南京航空航天大学, 2012.Zhu Y. Research on control and simulation of launch technology for carrier-based[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2012. [38] 张鑫. 舰载机拦阻着舰动力学分析及仿真[D]. 西安: 西北工业大学, 2007.Zhang X. Dynamic analysis and simulation of carrier aircraft arrested deck-landing[D]. Xi'an: Northwestern Polytechnical University, 2007. [39] 徐胜, 徐元铭, 王永庆. 舰载机拦阻着舰建模仿真研究[J]. 舰载机设计, 2009, 29(5): 5-8.Xu S, Xu Y M, Wang Y Q. Carrier-based aircraft landing process modeling and simulation study[J]. Aircraft Design, 2009, 29(5): 5-8. [40] 张雷, 冯蕴雯, 薛小锋, 等. 舰载机蒸汽弹射动力学仿真分析[J]. 航空计算技术, 2013, 42(6): 29-33.Zhang L, Feng Y W, Xue X F, et al. Dynamics simulation of carrier-based aircraft steam catapult[J]. Aeronautical Computing Technique, 2013, 42(6): 29-33. [41] 马善智. 舰载机偏心拦阻过程动力学分析与仿真[D]. 南京: 南京航空航天大学, 2012.Ma S Z. Analysis and simulation of carrier aircraft off-center arresting landing process[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2012. [42] 王文秀, 祝华远, 孙鲁青, 等. 机务准备中的保障装备配置优化分析[J]. 科学技术与工程, 2009(21): 6601-6602.Wang W X, Zhu H Y, Sun L Q, et al. Optimum configuration of equipment in maintenance[J]. Science Technology and Engineering, 2009(21): 6601-6602. [43] 吕晓峰, 李保刚, 周玉柱. 基于遗传算法的航空弹药保障人员优化配置[J]. 计算机与现代化, 2011, 1(10): 11-14.Lü X F, Li B G, Zhou Y Z. Optimized collocation of airborne ammunition support personnel based on genetic algorithm[J]. Computer and Modernization, 2011, 1(10): 11-14. [44] 周鑫磊, 孟祥印, 解学参, 等. 基于排队论的大型舰船甲板弹射器数量研究[J]. 中国舰船研究, 2011, 6(2): 15-18.Zhou X L, Meng X Y, Xie X C, et al. Investigation into deck catapults quantity of large ship by using queuing theory[J]. Chinese Journal of Ship Research, 2011, 6(2): 15-18. [45] 孟祥印. 飞行甲板总布置设计中的若干问题研究[D]. 哈尔滨: 哈尔滨工程大学, 2011.Meng X Y. The research on some key problems in general arrangement design of flight deck[D]. Harbin: Harbin Engineering University, 2011. [46] 王健, 谢伟, 熊治国. 基于多目标遗传算法的飞行甲板参数化设计优化方法[J]. 中国舰船研究, 2013, 8(1): 7-12.Wang J, Xie W, Xiong Z G. Parametric optimization of the flight deck design based on the multi-objective genetic algorithm[J]. Chinese Journal of Ship Research, 2013, 8(1): 7-12. [47] 林华, 占明锋, 周丰. 舰载机回收任务的优化调度算法及仿真[J]. 海军工程大学学报, 2008, 20(1): 50-54.Lin H, Zhan M F, Zhou F. Optimization schedule algorithm and simulation to recycle planes on carrier[J]. Journal of Naval University of Engineering, 2008, 20(1): 50-54. [48] 吕晓峰, 郭小威, 王云飞. 基于遗传算法的舰载机弹药调度次序[J]. 兵工自动化, 2011, 30(8): 10-12.Lü X F, Guo X W, Wang Y F. Sequence analyzing of carrier-based aircraft ammunition scheduling based on genetic algorithms[J]. Ordnance Industry Automation, 2011, 30(8): 10-12. [49] 陈希林, 季新源, 粟嘉立. 航空弹药挂载方案优化模型及其遗传算法求解[J]. 系统仿真学报, 2009, 18(16): 5175-5178.Chen X L, Ji X Y, Su J L. Carry scheme optimal model of airborne ammunition and its solution based on GA[J]. Journal of System Simulation, 2009, 18(16): 5175-5178. [50] 马登武, 郭小威, 邓力. 基于改进蚁群算法的舰载机弹药调度[J]. 系统仿真学报, 2012, 24(6): 1207-1211.Ma D W, Guo X W, Deng L. Ammunition scheduling of carrier-based aircraft based on modified ant colony algorithm[J]. Journal of System Simulation, 2012, 24(6): 1207-1211. [51] 马登武, 郭小威, 吕晓峰. 基于改进遗传算法的舰载机弹药调度[J]. 计算机工程与应用, 2012, 48(8): 246-248.Ma D W, Guo X W, Lü X F. Modified genetic algorithms for scheduling scheme of carrier-based aircraft ammunition[J]. Computer and Engineering and Applications, 2012, 48(8): 246-248. [52] 栾孝丰, 谢君. 基于仿真优化的多机机务准备流程研究[J]. 计算机与数字工程, 2010, 15(12): 10-17.Luan X F, Xie J. Research on multi-aircrafts preparation process based on simulation optimization[J]. Computer and Digital Engineering, 2010, 15(12): 10-17. [53] 冯强, 曾声奎, 康锐. 不确定条件下舰载机动态调度仿真与优化方法[J]. 系统仿真学报, 2011, 23(7): 1497-1501. Feng Q, Zeng S K, Kang R. Dynamic scheduling simulation and optimization of carrier aircraft under uncertainty[J]. Journal of System Simulation, 2011, 23(7): 1497-1501. [54] 刘钦辉, 邱长华, 王能建. 考虑空间约束的舰载机作业调度模型研究[J]. 哈尔滨工程大学学报, 2012, 12(11): 1435-1439.Liu Q H, Qiu C H, Wang N J. Study on ship-based aircraft operation scheduling model considering spatial restriction[J]. Journal of Harbin Engineering University, 2012, 12(11): 1435-1439. [55] 张思. 舰载机自动布列方法的研究[D]. 哈尔滨: 哈尔滨工程大学, 2012.Zhang S. Research on the automatic layout model of the aircraft[D]. Harbin: Harbin University of Engineering, 2012. [56] 王绍华. 海军机场飞行保障流程仿真及优化[D]. 哈尔滨: 哈尔滨工程大学, 2012.Wang S H. Simulation and optimization for flight maintenance process of navy airport[D]. Harbin: Harbin University of Engineering, 2012. [57] 王国庆. 舰载机甲板调度路径优化方法研究[D]. 哈尔滨: 哈尔滨工程大学, 2012.Wang G Q. Optimization method of aircraft scheduling path on deck[D]. Harbin: Harbin University of Engineering, 2012. [58] 魏昌全, 陈春良, 王保乳. 基于任务的连续出动舰载机航空保障重调度研究[J]. 指挥控制与仿真, 2012, 34(3): 23-26.Wei C Q, Chen C L, Wang B R. Rescheduling study of aircraft support of running launch aircraft on carrier based on mission[J]. Command Control & Simulation, 2012, 34(3): 23-26. [59] 魏昌全, 陈春良, 王保乳. 基于出动方式的舰载机航空保障调度模型[J]. 海军航空工程学院学报, 2012, 27(1): 111-114.Wei C Q, Chen C L, Wang B R. Research on the aircraft support scheduling model of carrier-based aircraft based on launch model[J]. Journal of Naval Aeronautical and Astronautical University, 2012, 27(1): 111-114. [60] 李耀宇, 朱一凡, 齐鸣, 等. 舰载机甲板布列调运优化方法研究[J]. 指挥控制与仿真, 2013, 35(2): 125-131.Li Y Y, Zhu Y F, Qi M, et al. An overview of aircraft allocation and transferring on carrier flight-deck[J]. Command Control & Simulation, 2013, 35(2): 125-131. [61] 韩维,苏析超, 陈俊锋. 舰载机多机一体化机务保障调度方法[J]. 系统工程与电子技术, 2015, 37(4): 809-816.Han W, Su X C, Chen J F. Integrated maintenance support scheduling method of multi carrier aircrafts[J]. Systems Engineering and Electronics, 2015, 37(4): 809-816. [62] 李耀宇, 朱一凡, 李群. 基于Legendre伪谱法的UGV避障路径规划[J]. 指挥控制与仿真, 2012, 34(4): 124-127.Li Y Y, Zhu Y F, Li Q. Legendre pseudospectral path planning method for UGV obstacle avoidance[J]. Command Control & Simulation, 2012, 34(4): 124-127. [63] Wu Y, Qu X J. Path planning for taxi of carrier aircraft launching[J]. Science China Technological Sciences, 2013, 56(6): 1561-1570. [64] 司维超, 齐玉东, 韩维. 基于融合Dijkstra的凸壳算法的舰载机机库调运规划[J]. 系统工程与电子技术, 2015, 37(3): 583-588.Si W C, Qi Y D, Han W. Carrier plane transportation in hangar based on convex hull algorithm combined with Dijkstra[J]. Systems Engineering and Electronics, 2015, 37(3): 583-588. [65] 张智, 林圣琳, 朱齐丹, 等. 考虑运动学约束的不规则目标遗传避碰规划算法[J]. 航空学报, 2015, 36(4): 1348-1358.Zhang Z, Lin S L, Zhu Q D, et al. Genetic collision avoidance planning algorithm for irregular shaped object with kinematics constraint[J]. Acta Aeronautica et Astronautica Sinica, 2015, 36(4): 1348-1358. [66] 张智, 林圣琳, 夏桂华, 等. 舰载机甲板调运过程避碰路径规划研究[J]. 哈尔滨工程大学学报, 2014, 35(1): 9-15.Zhang Z, Lin S L, Xia G H, et al. Collision avoidance path planning for an aircraft in scheduling process on deck[J]. Journal of Harbin Engineering University, 2014, 35(1): 9-15. [67] 张智, 林圣琳, 邱兵, 等. 舰载机牵引系统甲板调运避碰路径规划[J]. 系统工程与电子技术, 2014, 36(8): 1551-1557.Zhang Z, Lin S L, Qiu B, et al. Collision avoidance path planning of carrier aircraft traction system in dispatching on deck[J]. Systems Engineering and Electronics, 2014, 36(8): 1551-1557. [68] 李耀宇, 朱一凡, 贾全, 等. 基于排队网络的舰载机甲板调运优化调度策略生成方法[J]. 海军工程大学学报, 2013, 25(5): 26-30.Li Y Y, Zhu Y F, Jia Q, et al. Queueing network-based optimal scheduling for carrier aircraft on flight deck[J]. Journal of Naval University of Engineering, 2013, 25(5): 26-30. [69] 王云翔, 毕玉泉, 杨茂胜, 等. 基于空间约束的舰载机出库调度[J]. 指挥控制与仿真, 2015, 37(1): 107-111.Wang Y X, Bi Y Q, Yang M S, et al. Shipboard aircraft scheduling based on space constraint[J]. Command Control & Simulation, 2105, 37(1): 107-111. [70] 刘亚杰, 李忠猛, 谢君. 基于改进遗传算法的舰载机出库调度优化方法[J]. 火力与指挥控制, 2015, 40(6): 57-60.Liu Y J, Li Z M, Xie J. Optimized method of carrier-borne aircrafts exporting scheduling based on improved genetic algorithm[J]. Fire Control & Command Control, 2015, 40(6): 57-60. [71] 苏析超,李聪颖,陈志刚. 混合差分进化算法在舰载机出动调度中的应用[J]. 计算机仿真, 2015, 32(4): 74-78.Su X C, Li C Y, Chen Z G. Hybrid differential evolution algorithm for sortie scheduling of carrier aircraft[J]. Computer Simulation, 2015, 32(4): 74-78. [72] 李耀宇, 朱一凡, 杨峰, 等.基于逆向强化学习的舰载机甲板调度优化方案生成方法[J]. 国防科技大学学报, 2013, 35(4): 171-175.Li Y Y, Zhu Y F, Yang F, et al. Inverse reinforcement learning based optimal schedule generation approach for carrier aircraft on flight deck[J]. Journal of National University of Defense Technology, 2013, 35(4): 171-175.
2017, Vol. 37 
