不确定性工时下甲板作业的前摄性鲁棒调度

万兵; 苏析超; 郭放; 韩维; 梁勇

doi:10.7527/S1000-6893.2021.25971

航空学报 >

2022 , Vol. 43 >Issue 12: 325971 - 325971

DOI: https://doi.org/10.7527/S1000-6893.2021.25971

电子电气工程与控制

不确定性工时下甲板作业的前摄性鲁棒调度

万兵 ,
苏析超 ,
郭放 ,
韩维 ,
梁勇

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海军航空大学, 烟台 264001

收稿日期: 2021-06-17

修回日期: 2021-08-07

网络出版日期: 2021-09-08

基金资助

海军装备预研项目

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Proactive robust scheduling of aircraft carrier flight deck operations with uncertain activity durations

WAN Bing ,
SU Xichao ,
GUO Fang ,
HAN Wei ,
LIANG Yong

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Naval Aviation University, Yantai 264001, China

Received date: 2021-06-17

Revised date: 2021-08-07

Online published: 2021-09-08

Supported by

Naval Equipment Pre-research Project

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摘要

针对舰载机甲板作业流程复杂、资源受限、工时不确定等特点，为提升周期时限约束下机队作业调度的鲁棒性，研究了不确定性工时下甲板作业的前摄性鲁棒调度方法。首先将机队作业抽象为不确定性资源受限下的多项目调度问题，考虑时空及多机间工序交叉耦合约束后构建了混合整数规划模型；其次针对不确定性工时的概率分布特性，提出基于机群按时完成概率、最大完工期望和方差等综合指标的鲁棒性目标函数，建立了甲板集中式保障前摄性鲁棒调度模型，提出了三阶段鲁棒调度生成机制与预约束策略（C^PC），并设计了结合双种群遗传优化和自适应变邻域局部优化的I-Memetic优化算法，采用Monte Carlo模拟对鲁棒性基准调度作了验证。实验表明，前摄性鲁棒调度能较好抑制在甲板作业周期内工时不确定性扰动，确保甲板作业鲁棒运行；在确定性与鲁棒性调度仿真中，提出的算法显著优于其它相关智能优化算法，而在鲁棒性调度策略中C^PC策略最佳。

关键词： 舰载机; 甲板作业; 不确定工时; 鲁棒性调度; 资源受限项目调度模型; I-Memetic

本文引用格式

万兵 , 苏析超 , 郭放 , 韩维 , 梁勇 . 不确定性工时下甲板作业的前摄性鲁棒调度[J]. 航空学报, 2022 , 43(12) : 325971 -325971 . DOI: 10.7527/S1000-6893.2021.25971

Abstract

In view of the complex procedures, resource constraints, and uncertain activity durations of carrier-based aircraft deck operations, this paper proposes a proactive robust scheduling method of deck operations with uncertain durations to improve the robustness of fleet operation scheduling under cycle time constraints. First, the aircraft fleet operation is abstracted as a resource-constrained multi-project scheduling problem with uncertain durations, and a mixed-integer programming model is constructed after considering the constraints of time, space, and cross-coupling between multi-aircraft operation. Then, considering the characteristics of probability distribution of uncertain durations, a robust objective function based on comprehensive indicators such as the on-time completion probability, maximum completion expectation and variance of the fleet deck operation is proposed, and a proactive robust scheduling model for the centralized support is established. The three-stage robust scheduling generation mechanism and pre-constraint strategy (C^PC) are given, and an I-Memetic optimization algorithm combining dual-population Genetic operator and adaptive variable neighborhood local operator is designed. Finally, Monte Carlo simulation is used to verify the robust deck operation benchmark scheduling. Experiments show that proactive robust scheduling can better suppress the disturbance of uncertain activity durations during the deck operation cycle, and ensure the smooth operation with robust scheduling scheme. In the deterministic and robust scheduling simulation, the algorithm proposed is significantly better than other related intelligent optimization algorithms, and the C^PC strategy is the best one among the robust scheduling strategies.

Key words： carrier aircraft; deck operation; uncertain activity duration; robust scheduling; resource corstrained project scheduling problem; I-Memetic

参考文献

[1] 王能建, 刘钦辉, 李江. 舰载机出动回收能力仿真研究[M]. 北京:科学出版社, 2018. WANG N J, LIU Q H, LI J. Simulation research on dispatch recovery capability of carrier-based aircraft[M]. Beijing:Science Press, 2018(in Chinese).
[2] RYAN J C. Evaluating safety protocols for manned unmanned environments through agent based simulation[D]. Cambridge:Massachusetts Institute of Technology, 2014.
[3] 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.
[4] MICHINI B, HOW J. A human-interactive course of action planner for aircraft carrier deck operations:AIAA-2011-1515[R]. Reston:AIAA, 2011.
[5] ZHENG M, YANG F Q, DONG Z P, et al. Carrier-borne aircrafts aviation operation automated scheduling using multiplicative weights apprenticeship learning[J]. International Journal of Advanced Robotic Systems, 2019, 16(1):172988141982891.
[6] MURAVEV D, HU H, RAKHMANGULOV A, et al. Multi-agent optimization of the intermodal terminal main parameters by using AnyLogic simulation platform:Case study on the Ningbo-Zhoushan Port[J]. International Journal of Information Management, 2021, 57:102133.
[7] WU Y, QU X J. Obstacle avoidance and path planning for carrier aircraft launching[J]. Chinese Journal of Aeronautics, 2015, 28(3):695-703.
[8] ZHANG Z, LIN S L, DONG R, et al. Designing a human-computer cooperation decision planning system for aircraft carrier deck scheduling:AIAA-2015-1111[R]. Reston:AIAA, 2015.
[9] YU L F, ZHU C, SHI J M, et al. An extended flexible job shop scheduling model for flight deck scheduling with priority, parallel operations, and sequence flexibility[J]. Scientific Programming, 2017, 2017:2463252.
[10] WANG X W, LIU J, SU X C, et al. A review on carrier aircraft dispatch path planning and control on deck[J]. Chinese Journal of Aeronautics, 2020, 33(12):3039-3057.
[11] QI C, WANG D. Dynamic aircraft carrier flight deck task planning based on HTN[J]. IFAC-PapersOnLine, 2016, 49(12):1608-1613.
[12] CUI R W, HAN W, SU X C, et al. A dual population multi-operator genetic algorithm for flight deck operations scheduling problem[J]. Journal of Systems Engineering and Electronics, 2021, 32(2):331-346.
[13] 苏析超, 韩维, 萧卫, 等. 基于Memetic算法的舰载机舰面一站式保障调度[J]. 系统工程与电子技术, 2016, 38(10):2303-2309. SU X C, HAN W, XIAO W, et al. Pit-stop support scheduling on deck of carrier plane based on Memetic algorithm[J]. Systems Engineering and Electronics, 2016, 38(10):2303-2309(in Chinese).
[14] 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, 33(11):1435-1439, 1452. 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, 33(11):1435-1439, 1452(in Chinese).
[15] YUAN P L, HAN W, SU X C, et al. A dynamic scheduling method for carrier aircraft support operation under uncertain conditions based on rolling horizon strategy[J]. Applied Sciences, 2018, 8(9):1546.
[16] SU X C, HAN W, WU Y, et al. A robust scheduling optimization method for flight deck operations of aircraft carrier with ternary interval durations[J]. IEEE Access, 6:69918-69936.
[17] 李亚飞, 吴庆顺, 徐明亮, 等. 基于强化学习的舰载机保障作业实时调度方法[J]. 中国科学:信息科学, 2021, 51(2):247-262. LI Y F, WU Q S, XU M L, et al. Real-time scheduling for carrier-borne aircraft support operations:A reinforcement learning approach[J]. Scientia Sinica (Informationis), 2021, 51(2):247-262(in Chinese).
[18] BALOUKA N, COHEN I. A robust optimization approach for the multi-mode resource-constrained project scheduling problem[J]. European Journal of Operational Research, 2021, 291(2):457-470.
[19] HAUDER V A, BEHAM A, RAGGL S, et al. Resource-constrained multi-project scheduling with activity and time flexibility[J]. Computers & Industrial Engineering, 2020, 150:106857.
[20] VAN DE VONDER S, DEMEULEMEESTER E, HERROELEN W. Proactive heuristic procedures for robust project scheduling:An experimental analysis[J]. European Journal of Operational Research, 2008, 189(3):723-733.
[21] BOLD M, GOERIGK M. A compact reformulation of the two-stage robust resource-constrained project scheduling problem[J]. Computers & Operations Research, 2021, 130:105232.
[22] ZENG B, ZHAO L. Solving two-stage robust optimization problems using a column-and-constraint generation method[J]. Operations Research Letters, 2013, 41(5):457-461.
[23] 苏析超, 韩维, 张勇, 等. 考虑人机匹配模式的舰载机甲板机务勤务保障调度算法[J]. 航空学报, 2018, 39(12):222314. SU X C, HAN W, ZHANG Y, et al. Scheduling algorithm for maintenance and service support of carrier-based aircraft on flight deck with different man-aircraft matching patterns[J]. Acta Aeronautica et Astronautica Sinica, 2018, 39(12):222314(in Chinese).
[24] BRUNI M E, BERALDI P, GUERRIERO F, et al. A heuristic approach for resource constrained project scheduling with uncertain activity durations[J]. Computers & Operations Research, 2011, 38(9):1305-1318.
[25] GEIGER M J. A multi-threaded local search algorithm and computer implementation for the multi-mode, resource-constrained multi-project scheduling problem[J]. European Journal of Operational Research, 2017, 256(3):729-741.
[26] 蒋婷婷, 韩维, 苏析超. 基于改进DE算法的舰载机保障调度优化[J]. 计算机仿真, 2018, 35(10):51-56. JIANG T T, HAN W, SU X C. Optimization of carrier aircraft support scheduling based on improved DE algorithm[J]. Computer Simulation, 2018, 35(10):51-56(in Chinese).
[27] ZHOU Y Z. A modified differential evolution algorithm for resource constrained multi-project scheduling problem[J]. Journal of Computers, 2014, 9(8):1922-1927.
[28] 李敬花, 胡载萍, 吕慧超, 等. 多资源约束下海工装备多项目调度优化[J]. 哈尔滨工程大学学报, 2013, 34(10):1214-1220. LI J H, HU Z P, LYU H C, et al. Optimization of multi-resource constrained offshore equipment multi-project scheduling[J]. Journal of Harbin Engineering University, 2013, 34(10):1214-1220(in Chinese).
[29] BALLESTÍN F. When it is worthwhile to work with the stochastic RCPSP?[J]. Journal of Scheduling, 2007, 10(3):153-166.
[30] 郑晓龙, 王凌. 随机资源约束项目调度问题基于序的果蝇算法[J]. 控制理论与应用, 2015, 32(4):540-545. ZHENG X L, WANG L. An order-based fruit fly optimization algorithm for stochastic resource-constrained project scheduling[J]. Control Theory & Applications, 2015, 32(4):540-545(in Chinese).

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