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1. 武警工程大学 装备管理与保障学院, 陕西 西安 710086
2. 大连海事大学 航运经济与管理学院, 辽宁 大连 116026
3. 武警研究院, 北京 100020
4. 中国海警局, 北京 100089
Received:26 June 2024,
Published Online:07 May 2025,
Published:31 May 2025
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Chuang ZHANG, Chaoqiang WEI, Yantong LI, et al. Ship-drone Collaboration Routing for Island and Reef Cruise[J]. Acta Armamentarii, 2025, 46(5): 240505.
Chuang ZHANG, Chaoqiang WEI, Yantong LI, et al. Ship-drone Collaboration Routing for Island and Reef Cruise[J]. Acta Armamentarii, 2025, 46(5): 240505. DOI: 10.12382/bgxb.2024.0505.
为进一步提升海上巡航效率
对基于舰船和无人机动态协同的岛礁巡航路径规划问题进行研究。该问题具有舰机动态协同、时空精确耦合、离散与连续变量同时优化等复杂特点。构建一种混合整数2阶锥规划模型以最小化巡航任务完成时间
实现对舰船航行路径、无人机飞行路径及无人机起降位置等的组合优化。应用自适应大邻域搜索(Adaptive Large Neighborhood Search
ALNS)算法
设计3种破坏算子、2种修复算子及其自适应机制进行求解。基于某海域若干岛礁数据开展案例分析
证明舰机协同模式下巡航时间可减少45%以上。算例实验结果表明
ALNS算法可在90s内求解最多包含80个岛礁的算例
其求解能力和效率显著优于CPLEX求解器和两阶段启发式算法。新提出的基于舰机协同的岛礁巡航路径规划方法
为高效遂行海上维权执法任务提供了方法参考。
The route planning issue for island and reef cruise based on the dynamic collaboration among ships and drones is investigated to enhance the efficiency of maritime cruise. The issue is characterized by the dynamic cooperation among ships and drones
the precise spatio-temporal coupling
and the simultaneous optimization of discrete and continuous variables. Accordingly
a mixed-integer second-order cone programming model to minimize the mission completion time is developed for a combined optimization of the ship navigation path
the drone flight trajectory
and the drone takeoff and landing positions. The adaptive large neighborhood search (ALNS) algorithm is applied to design three destruction operators
two repair operators
and their adaptive mechanisms. A case analysis is conducted based on data from several islands and reefs in a specific maritime area
demonstrating that the cruise time can be reduced by more than 45% under the ship-drone coordination mode. The computational results indicate that the ALNS algorithm can solve the instances with up to 80 islands and reefs within 90 seconds
significantly outperforming the CPLEX solver and the two-stage heuristic algorithm in terms of solution quality and efficiency. The proposed route planning method for island and reef cruise based on ship-drone collaboration provides a reference for efficiently conducting maritime rights protection and law enforcement missions.
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LI Y T , ZHANG C , TANG L H . Review on mothership-vehicle collaborative routing problem [J ] . Control and Decision , 2025 , 40 ( 2 ): 387 - 403 . (in Chinese)
LIU B L , WANG Y D , LI Z C , et al. An exact method for vessel emission monitoring with a ship-deployed heterogeneous fleet of drones [J ] . Transportation Research Part C , 2023 , 153 : 104198 .
侯云霞 . 船载无人机协同监测港口船舶大气污染路径规划 [D ] . 大连 : 大连海事大学 , 2022 .
HOU Y X . Synergistic path planning for ship-deployed multiple UAVs to monitor vessel pollution in ports [D ] . Dalian : Dalian Maritime University , 2022 . (in Chinese)
SHEN L X , HOU Y X , YANG Q . Synergistic path planning for ship-deployed multiple UAVs to monitor vessel pollution in ports [J ] . Transportation Research Part D , 2022 , 110 : 103415 .
LI Y T , WANG X Q , ZHANG S , et al. Vessel-UAV collaborative routing problem for offshore oil and gas fields inspection [C ] //Proceedings of 2023 IEEE International Conference on Networking, Sensing and Control. Marseille, France:IEEE , 2023 .
TANG L H , LI Y T . A new formulation for the multi-period vessel-drone routing problem [C ] //Proceedings of 2023 IEEE International Conference on Networking, Sensing and Control. Marseille, France:IEEE , 2023 .
LI Y T , WANG S J , ZHOU S S , et al. A mathematical formulation and a tabu search heuristic for the joint vessel-UAV routing problem [J ] . Computers & Operations Research , 2024 ,169:106723.
XUE G Q , LI Y T , WANG Z . Vessel-UAV collaborative optimization for the offshore oil and gas pipelines inspection [J ] . International Journal of Fuzzy Systems , 2023 , 25 ( 1 ): 382 - 394 .
AMOROSI L , PUERTO J , VALVERDE C . Coordinating drones with mothership vehicles: the mothership and drone routing problem with graphs [J ] . Computers and Operations Research , 2021 , 136 : 105445 .
AMOROSI L , PUERTO J , VALVERDE C . A multiple-drone arc routing and mothership coordination problem [J ] . Computers and Operations Research , 2023 , 159 : 106322 .
ZHANG X P , ZHANG F R , TANG Z . A MILP model on coordinated coverage path planning system for UAV-ship hybrid team scheduling software [J ] . The Journal of Systems & Software , 2023 , 206 : 111854 .
朱益民 . 多无人机舰机协同任务分配 [D ] . 合肥 : 合肥工业大学 , 2016 .
ZHU Y M . Cooperative task allocation method for ship and UAVs [D ] . Hefei : Hefei University of Technology , 2016 . (in Chinese)
马华伟 , 朱益民 , 胡笑旋 . 基于粒子群算法的无人机舰机协同任务规划 [J ] . 系统工程与电子技术 , 2016 , 38 ( 7 ): 1583 - 1588 .
MA H W , ZHU Y M , HU X X . Cooperative task planning for ship and UAVs based on particle swarm optimization algorithm [J ] . Systems Engineering and Electronics , 2016 , 38 ( 7 ): 1583 - 1588 . (in Chinese) DOI: 10.3969/j.issn.1001-506X.2016.07.16 http://doi.org/10.3969/j.issn.1001-506X.2016.07.16 <p align="justify">Cooperative task planning for ship and unmanned aerial vehicles (UAVs) (CPSU)is a new technology which can make full use of the complementary advantages between ship and UAVs to make task planning cooperatively. It is a new focus on the UAVs&rsquo; task planning problem, and it has great influence on improving the navy combat capability. A mathematical model of CPSU is built, and then a selfadaptive particle swarm optimization (APSO) algorithm is introduced to solve it. The algorithm can self adaptively change the inertia weight, which can avoid the PSO trapping into the local optimum better. The experiment shows that the APSO algorithm solves the problem more effectively than the standard PSO and the PSO with the constrict factor.</p>
XIA J , WANG K , WANG S A . Drone scheduling to monitor vessels in emission control areas [J ] . Transportation Research Part B: Methodological , 2019 , 119 : 174 - 196 .
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SUKSEE S , SINDHUCHAO S . GRASP with ALNS for solving the location routing problem of infectious waste collection in the Northeast of Thailand [J ] . International Journal of Industrial Engineering Computations , 2021 , 12 ( 3 ): 305 - 320 .
RAHIMI S K , RAHIMI D . An improved ALNS for hybrid pickup and drones delivery system in disaster by penalizing deprivation time [J ] . Computers & Operations Research , 2024 ,170: 106722.
CHANG X N , SHI J M , LUO Z H , et al. Adaptive large neighborhood search algorithm for multi-stage weapon target assignment problem [J ] . Computers & Industrial Engineering , 2023 , 181 : 109303 .
MARA S T W , NORCAHVO R , JODIAWAN P , et al. A survey of adaptive large neighborhood search algorithms and applications [J ] . Computers & Operations Research , 2022 ,146:105903.
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WEN X P , WU G H . Heterogeneous multi-drone routing problem for parcel delivery [J ] . Transportation Research Part C , 2022 , 141 : 103763 .
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