Research on Optimal Scheduling Model of Repair Resources for Maritime Ships

doi:10.12382/bgxb.2025.0167

Abstract

Abstract:

In response to the issue of providing emergency repair support for damaged ships at sea，this paper proposes an optimal scheduling model for repairing the ships at sea and solves it using an improved multi-dimensional dynamic list planning algorithm （MPLDS）.The basic process of emergency repair of ship offshore equipment is established，and a task-resource optimal scheduling constraint model is proposed，which is divided into two parts：the effect-based action optimisation method and the constraint model of optimal scheduling.The improved MPLDS is applied to solve the constraint model，the time，cost and the importance of task and support platform in the process of optimal scheduling are fully taken into account，and the calculation examples is analyzed to verify the accuracy.The results show that the improved MPLDS algorithm makes full use of the priority mediation method to solve the optimal scheduling constraint model，which can satisfy the basic demands of the support plan maker in terms of all aspects of considerations，and realise the efficient repair support for damaged ships at sea.

Key words: maritime ship emergency repair, optimal scheduling model, multidimensional dynamic list planning algorithm, priority mediation

ZHANG Gouzhou, GUO Jingjing, XIA Zichao, ZHAO Bo, CHEN Hao. Research on Optimal Scheduling Model of Repair Resources for Maritime Ships[J]. Acta Armamentarii, 2025, 46(S1): 250167-.

Figures/Tables 6

References 21

[1]	刘盛钰, 齐小刚, 刘立芳. 伴随维修资源配置与任务调度的多目标联合优化[J]. 兵工学报, 2024, 45(7):2442-2450. doi: 10.12382/bgxb.2023.0337
	LIU S Y, QI X G, LIU L F. Multi-objective joint optimization of accompanying maintenance resource allocation and task scheduling[J]. Acta Armamentarii, 2024, 45 (7):2442-2450. (in Chinese)
[2]	MCLAIN J. Adopt laser cleaning for navy maintenance[J]. United States Naval Institute Proceedings, 2024, 150(2):1452.
[3]	MUMRPHY H. A cinderella industry:private and nationalized ship-repair companies in britain,1970-1986[J]. International Journal of Maritime History, 2024, 36(4):897-923.
[4]	VOROBYOVA A A, BESSONOVA V O. Bending of the ship’s hull with the help of inflatable elastic shells.Compensation of welding stresses that occur during ship repair[J]. Transactions of the Krylov State Research Centre, 2024, 4(410):29-37.
[5]	于上媛, 刘晓冰, 薛方红. 基于灰色层次分析法的船舶修理项目优先级评价研究[J]. 项目管理技术, 2016, 14(7):122-128.
	YU S Y, LIU X B, XUE F H. Research on priority evaluation of ship repair projects based on grey analytic hierarchy process[J]. Project Management Technology, 2016, 14(7):122-128. (in Chinese)
[6]	荆海东, 李康康, 陈雷, 等. 大型半潜船艉轴承磨损分析与修理[J]. 船舶工程, 2023, 45(8):135-141.
	JIHG H D, LI K K, CHEN L, et al. Wear analysis and repair of stern bearings for large semi-submersible ships[J]. Ship Engineering, 2023, 45(8):135-141. (in Chinese)
[7]	哈尔滨工程大学, 哈尔滨工程大学青岛船舶科技有限公司. 一种基于北斗卫星的船舶远程支援系统及其支援方法:CN202111068621.X[P].2024-07-26.
	Qingdao Ship Technology Co.,Ltd. of Harbin Engineering University. A ship remote support system based on beidou satellite and its support method:CN202111068621.X[P].2024-07-26. (in Chinese)
[8]	李冬琴, 姚震球, 管义锋. 海洋平台支援船的改进协同优化设计[J]. 江苏科技大学学报(自然科学版), 2013, 27(1):10-13.
	LI D Q, YAO Z Q, GUAN Y F. Improved collaborative optimization design of offshore platform support vessels[J]. Journal of Jiangsu University of Science and Technology (Natural Science Edition), 2013, 27(1):10-13. (in Chinese)
[9]	王俊龙, 袁伟, 管旭军. 舶装备远程维修技术支援知识库系统研究[J]. 软件导刊, 2018, 17(10):137-140.
	WANG J L, YUAN W, GUAN X J. Research on knowledge base system for remote maintenance technical support of ship equipment[J]. Software Guide, 2018, 17(10):137-140. (in Chinese)
[10]	张天成. 秦皇岛港船舶调度优化研究[D]. 秦皇岛: 燕山大学, 2022.
	ZHANG T C. Research on ship scheduling optimization for Qinhuangdao port[D]. Qinhuangdao: Yanshan University, 2022. (in Chinese)
[11]	武越, 丁航奇, 何昊, 等. 多任务优化算法及应用研究综述[J]. 计算机应用, 2024, 44(5):1338-1347. doi: 10.11772/j.issn.1001-9081.2024020209
	WU Y, DING H Q, HE H, et al. A survey of multi-task optimization algorithms and their applications[J]. Journal of Computer Applications, 2024, 44(5):1338-1347.
[12]	齐丁丁, 徐斌, 赵英俊, 等. 基于复杂约束的地面防空作战装备支援保障节点选址问题研究[J]. 空军工程大学学报, 2024, 25(5):90-97.
	QI D D, XU B, ZHAO Y J, et al. Research on location problem of ground air defense combat equipment support nodes based on complex constraints[J]. Journal of Air Force Engineering University, 2024, 25(5):90-97. (in Chinese)
[13]	SONG H N, HAN X Y, LÜ J, et al. MPLDS:an integration of CP-ABE and local differential privacy for achieving multiple privacy levels data sharing[J]. Peer-to-Peer Networking and Applications, 2021, 15:369-385.
[14]	姚伟华. 基于MPLDS算法的非常规突发事件应急任务规划研究[D]. 西安: 西安理工大学, 2017.
	YAO W H. Research on emergency task planning for unconventional emergencies based on MPLDS algorithm[D]. Xi’an: Xi’an University of Technology, 2017. (in Chinese)
[15]	喇蕊芳, 薛芳明, 白鹏飞, 等. 基于“情景-任务”的重特大地质灾害救援装备调配优化[J]. 安全与环境学报, 2023, 23(5):1568-1578.
	LA R F, XUE F M, BAI P F, et al. Optimization of rescue equipment allocation for extraordinary geological disasters based on “scenario-task”[J]. Journal of Safety and Environment, 2023, 23(5):1568-1578. (in Chinese)
[16]	ZHANG H K, MA R, HE Z W. Project scheduling cost optimization based on resource transfer costs and robustness[J]. Computers and Operations Research, 2024, 161:106445.
[17]	SHAO J, CAO J, WANG C J, et al. Automatic measurement and comparison of normal eyelid contour by age and gender using image-based deep learning[J]. Ophthalmology Science, 2024, 4(5):100518.
[18]	DONG X Y, YANG R J, YE Y M, et al. Planning for green infrastructure by integrating multi-driver:Ranking priority based on accessibility equity[J]. Sustainable Cities and Society, 2024, 114:105767.
[19]	唐锐, 刘长毅, 张静. 浅谈精确打击火力体系与战场支援保障系统的关系[J]. 兵工学报, 2010, 31(增刊2):103-106.
	TANG R, LIU C Y, ZHANG J. Brief discussion on the relationship between precision strike firepower system and battlefield support guarantee system[J]. Acta Armamentarii, 2010, 31(S2):103-106. (in Chinese)
[20]	ZHAO J L, HOU S, ZHANG H, et al. Spatiotemporal variations and priority ranking of emerging contaminants in nanwan reservoir:A case study from the agricultural region in huaihe river basin in China[J]. Journal of Environmental Management, 2024, 368:122195.
[21]	LINDSTAD H E, SABDAAS I. Emission and fuel reduction for offshore support vessels through hybrid technology[J]. Journal of Ship Production and Design, 2016, 32:195-205.

任务	开始时间	结束时间	成本	支援平台
t₁	0	12.8	6.6	P₁，P₄
t₂	0	8.6	4.8	P₂，P₅
t₃	12.8	29.6	14.8	P₄，P₇
t₄	0	24.1	12.6	P₃
t₅	12.8	39.3	20.6	P₂
t₆	24.1	31.2	5.2	P₁
t₇	24.1	50.1	29.3	P₆，P₈，P₁₀
t₈	8.6	30.4	20.6	P₅，P₉
t₉	30.4	43.8	9.3	P₄，P₇
t₁₀	24.1	48.6	15.6	P₁₁
t₁₁	31.2	40.6	8.2	P₁，P₃
t₁₂	0	15.4	12.5	P₁₁，P₆
t₁₃	12.8	24.1	13.6	P₁，P₁₀
t₁₄	50.1	65.3	10.8	P₅，P₈
t₁₅	65.3	75.6	8.4	P₃，P₁₀
t₁₆	39.3	48.3	9.5	P₂，P₉
t₁₇	50.1	65.8	13.5	P₂，P₆
t₁₈	40.6	55.8	12.8	P₁，P₁₁
t₁₉	40.6	61.4	12.9	P₃
t₂₀	48.3	62.3	9.3	P₄，P₉

任务	开始时间	结束时间	成本	支援平台
t₁	0	12.8	6.6	P₁，P₄
t₂	0	8.6	4.8	P₂，P₅
t₃	12.8	29.6	14.8	P₄，P₇
t₄	0	24.1	12.6	P₃
t₅	12.8	39.3	20.6	P₂
t₆	24.1	31.2	5.2	P₁
t₇	24.1	50.1	29.3	P₆，P₈，P₁₀
t₈	8.6	30.4	20.6	P₅，P₉
t₉	30.4	43.8	9.3	P₄，P₇
t₁₀	24.1	48.6	15.6	P₁₁
t₁₁	31.2	40.6	8.2	P₁，P₃
t₁₂	0	15.4	12.5	P₁₁，P₆
t₁₃	12.8	24.1	13.6	P₁，P₁₀
t₁₄	50.1	65.3	10.8	P₅，P₈
t₁₅	65.3	75.6	8.4	P₃，P₁₀
t₁₆	39.3	48.3	9.5	P₂，P₉
t₁₇	50.1	65.8	13.5	P₂，P₆
t₁₈	40.6	55.8	12.8	P₁，P₁₁
t₁₉	40.6	61.4	12.9	P₃
t₂₀	48.3	62.3	9.3	P₄，P₉

任务	开始时间	结束时间	成本	支援平台
t₁	0	12.8	6.6	P₁，P₄
t₂	0	8.6	4.8	P₂，P₅
t₃	13.2	30.6	14.5	P₄，P₈
t₄	0	24.1	12.6	P₃
t₅	12.8	29.3	21.2	P₁，P₅
t₆	29.3	36.4	5.2	P₁
t₇	30.6	56.6	29.3	P₆，P₈，P₁₀
t₈	0	20.1	16.3	P₇，P₉
t₉	35.8	49.2	9.3	P₄，P₇
t₁₀	35.8	60.3	15.6	P₁₁
t₁₁	36.4	45.8	8.2	P₁，P₃
t₁₂	0	15.4	12.5	P₁₁，P₆
t₁₃	0	13.2	12.5	P₈，P₁₀
t₁₄	56.6	68.8	9.8	P₁，P₇，P₁₀
t₁₅	68.8	78.6	5.4	P₆，P₈
t₁₆	15.4	30.3	9.5	P₆，P₁₀
t₁₇	56.6	72.8	10.5	P₅
t₁₈	20.1	35.8	12.8	P₇，P₁₁
t₁₉	20.1	41.9	12.3	P₉
t₂₀	8.6	34.3	7.3	P₂

任务	开始时间	结束时间	成本	支援平台
t₁	0	12.8	6.6	P₁，P₄
t₂	0	8.6	4.8	P₂，P₅
t₃	13.2	30.6	14.5	P₄，P₈
t₄	0	24.1	12.6	P₃
t₅	12.8	29.3	21.2	P₁，P₅
t₆	29.3	36.4	5.2	P₁
t₇	30.6	56.6	29.3	P₆，P₈，P₁₀
t₈	0	20.1	16.3	P₇，P₉
t₉	35.8	49.2	9.3	P₄，P₇
t₁₀	35.8	60.3	15.6	P₁₁
t₁₁	36.4	45.8	8.2	P₁，P₃
t₁₂	0	15.4	12.5	P₁₁，P₆
t₁₃	0	13.2	12.5	P₈，P₁₀
t₁₄	56.6	68.8	9.8	P₁，P₇，P₁₀
t₁₅	68.8	78.6	5.4	P₆，P₈
t₁₆	15.4	30.3	9.5	P₆，P₁₀
t₁₇	56.6	72.8	10.5	P₅
t₁₈	20.1	35.8	12.8	P₇，P₁₁
t₁₉	20.1	41.9	12.3	P₉
t₂₀	8.6	34.3	7.3	P₂