Joint Optimization of Selective Maintenance Decision and Mission Assignment for Equipment Groups

doi:10.12382/bgxb.2022.0649

Abstract

Abstract:

In order to meet the requirement of combat mission, the selective maintenance and mission assignment of equipment groups are implemented simultaneously, which can effectively improve the overall combat effectiveness of equipment groups. For the independent optimization of selective maintenance decision and mission assignment, a joint optimization model of selective maintenance decision and mission assignment of equipment groups is constructed with the goal of maximizing the mission completion probability, and an environmental coefficient is introduced to represent the influence of the working environment of different sub-missions on the unit state. The mission completion probability of the unit is obtained by solving the Markov model, thus obtaining the completion probability of the sub-mission and the entire mission is obtained. A genetic algorithm based on random keys is used to solve the problem, and the influence of the environmental coefficient on the jointly optimized results is analyzed. The validities of the model and algorithm are verified through an example. The numerical analysis shows that considering the combat mission assignment in the selective maintenance decision can get better results. The model can provide theoretical guidance and technical support for equipment maintenance decision in the battlefield environment.

Key words: equipment groups, selective maintenance, mission assignment, joint optimization, genetic algorithm

CLC Number:

MA Weining, HU Qiwei, CHEN Jing, JIA Xisheng. Joint Optimization of Selective Maintenance Decision and Mission Assignment for Equipment Groups[J]. Acta Armamentarii, 2024, 45(2): 407-416.

Figures/Tables 13

References 23

[1]	RICE W F, CASSADY C R, NACHLAS J A. Optimal maintenance plans under limited maintenance time[C]//Proceedings of the Seventh Industrial Engineering Research Conference. Banff, Canada, 1998: 1-3.
[2]	SHAHRAKI A F, YADAV O P, VOGIATZIS C. Selective maintenance optimization for multi-state systems considering stochastically dependent components and stochastic imperfect maintenance actions[J]. Reliability Engineering and System Safety, 2020, 196: 106738. doi: 10.1016/j.ress.2019.106738 URL
[3]	XU Q Z, GUO L M, SHI H P, et al. Selective maintenance problem for series-parallel system under economic dependence[J]. Defence Technology, 2016, 12(5): 388-400. doi: 10.1016/j.dt.2016.04.004 URL
[4]	FAN M F, ZENG Z G, ZIO E, et al. Modeling dependent competing failure processes with degradation-shock dependence[J]. Reliability Engineering and System Safety, 2017, 165: 422-430. doi: 10.1016/j.ress.2017.05.004 URL
[5]	王海朋, 段富海, 马骏. 复杂系统的选择性维修模型和求解算法[J]. 北京航空航天大学学报, 2020, 46(12): 2264-2273.
	WANG H P, DUAN F H, MA J. Selective maintenance model and its solving algorithm for complex system[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(12):2264-2273. (in Chinese)
[6]	LIU Y, HUANG H Z. Optimal selective maintenance strategy for multi-state systems under imperfect maintenance[J] IEEE Transaction on Reliability, 2010, 59(2): 356-367. doi: 10.1109/TR.2010.2046798 URL
[7]	王少华, 张仕新, 李勇, 等. 不完全维修条件下复杂系统的选择性维修决策方法研究[J]. 兵工学报, 2018, 39(6): 1215-1224. doi: 10.3969/j.issn.1000-1093.2018.06.023
	WANG S H, ZHANG S X, LI Y, et al. Research on selective maintenance decision-making method of complex system considering imperfect maintenance[J]. Acta Armamentarii, 2018, 39(6): 1215-1224. (in Chinese)
[8]	TAMBE P P. Selective maintenance optimization of a multi-component system based on simulated annealing algorithm[J]. Procedia Computer Science, 2022, 200: 1412-1421. doi: 10.1016/j.procs.2022.01.342 URL
[9]	CAO W B, JIA X S, LIU Y, et al. Selective maintenance optimization for fuzzy multi-state systems[J]. Journal of Intelligent & Fuzzy Systems, 2018, 34(1): 105-121.
[10]	DAO C D, ZUO M J. Optimal selective maintenance for multi-state systems in variable loading conditions[J]. Reliability Engineering and System Safety, 2017, 166: 171-180. doi: 10.1016/j.ress.2016.11.006 URL
[11]	DIALLO C, AGHEZZAF E H, KHATAB A, et al. Optimal joint selective imperfect maintenance and multiple repairpersons assignment strategy for complex multicomponent systems[J]. International Journal of Production Research, 2019, 57(13): 4098-4117. doi: 10.1080/00207543.2018.1505060 URL
[12]	HASSEN S, GUPTA N, BARI A. A fuzzy approach for a multiobjective selective maintenance problem[J]. International Journal of Operations Research, 2015, 12(3):91-101. doi: 10.21307/ijor-2015-009 URL
[13]	KAMAL M, MODIBBO U M, ALARJANI A, et al. Neutrosophic fuzzy goal programming approach in selective maintenance allocation of system reliability[J]. Complex & Intelligent Systems, 2021, 7: 1045-1059.
[14]	CHAABANE K, KHATAB A, DIALLO C, et al. Integrated imperfect multi-mission selective maintenance and repairpersons assignment problem[J]. Reliability Engineering and System Safety, 2020, 199: 106895. doi: 10.1016/j.ress.2020.106895 URL
[15]	DIALLO C, AGHEZZAF E H, KHATAB A, et al. Optimal joint selective imperfect maintenance and multiple repairpersons assignment strategy for complex multicomponent systems[J]. International Journal of Production Research, 2019, 57(13): 4098-4117. doi: 10.1080/00207543.2018.1505060 URL
[16]	LIU L J, YANG J, KONG X F, et al. Multi-mission selective maintenance and repairpersons assignment problem with stochastic durations[J]. Reliability Engineering and System Safety, 2022, 219: 108209. doi: 10.1016/j.ress.2021.108209 URL
[17]	LIU W H, ZHENG X, GARG H. Multi-UAV cooperative task assignment based on orchard picking algorithm[J]. International Journal of Computational Intelligence Systems, 2021, 14(1): 1461-1467. doi: 10.2991/ijcis.d.210423.003 URL
[18]	王幸运, 田野, 强晓明, 等. 基于协同效能的反导作战任务分配模型[J]. 空军工程大学学报, 2013, 14(4): 27-31.
	WANG X Y, TIAN Y, QIANG X M, et al. Mission assignment model for anti-missile combat based on cooperative efficiency[J]. Journal of Air Force Engineering University (Natural Science Edition), 2013, 14(4): 27-31. (in Chinese)
[19]	ZHEN Z Y, ZHU P, XUE Y X, et al. Distributed intelligent self-organized mission planning of multi-UAV for dynamic targets cooperative search-attack[J]. Chinese Journal of Aeronautics, 2019, 32(12): 2706-2716. doi: 10.1016/j.cja.2019.05.012 URL
[20]	王慕鸿, 周智超, 张蓉, 等. 两栖攻击舰对空自防御作战火力分配模型[J]. 火力与指挥控制, 2020, 45(12): 127-131.
	WANG M H, ZHOU Z C, ZHANG R, et al. Fire assignment model of amphibious assault ship to air self-defense[J]. Fire Control & Command Control, 2020, 45(12): 127-131. (in Chinese)
[21]	JIA Z Y, YU J Q, AI X L, et al. Cooperative multiple task assignment problem with stochastic velocities and time windows for heterogeneous unmanned aerial vehicles using a genetic algorithm[J]. Aerospace Science and Technology, 2018, 76: 112-125. doi: 10.1016/j.ast.2018.01.025 URL
[22]	ZHU X N, YAN R, PENG R, et al. Optimal routing, aborting and hitting strategies of UAVs executing hitting the targets considering the defense range of targets[J]. Reliability Engineering and System Safety, 2021, 215: 107811. doi: 10.1016/j.ress.2021.107811 URL
[23]	刘宇. 多状态复杂系统可靠性建模及维修决策[D]. 成都: 电子科技大学, 2010.
	LIU Y. Multi-state complex system reliability modeling and maintenance decision[D]. Chengdu: University of Electronic Science and Technology of China, 2010. (in Chinese)

序号	α_m	N_m_,1	N_m_,2	K_m	N_m
1	1.4	2	1	2	3
2	1.0	1	2	2	3

序号	α_m	N_m_,1	N_m_,2	K_m	N_m
1	1.4	2	1	2	3
2	1.0	1	2	2	3

序号	单元类型	状态概率分布
序号	单元类型	1	2	3	4
1	1	0.13	0.23	0.30	0.34
2	1	0.10	0.12	0.46	0.32
3	1	0.12	0.05	0.26	0.57
4	2	0.10	0.27	0.27	0.36
5	2	0.32	0.50	0.13	0.05
6	2	0.16	0.30	0.26	0.28

序号	单元类型	状态概率分布
序号	单元类型	1	2	3	4
1	1	0.13	0.23	0.30	0.34
2	1	0.10	0.12	0.46	0.32
3	1	0.12	0.05	0.26	0.57
4	2	0.10	0.27	0.27	0.36
5	2	0.32	0.50	0.13	0.05
6	2	0.16	0.30	0.26	0.28

算法	迭代次数	最优值	平均值	标准差	计算时间/s
枚举法		0.8872			1.2078
	50	0.8872	0.8861	0.0016	0.1104
遗传算法	100	0.8872	0.8865	0.0012	0.2170
	150	0.8872	0.8871	0.0008	0.3301
	200	0.8872	0.8872	0.0000	0.4365