Optimization of Vehicle Maintenance Process Scheduling under Limited Resources

doi:10.3969/j.issn.1000-1093.2021.09.024

Abstract

Abstract: The tight schedules, a large number of tasks, and many emergencies will arise for the maintenance of vehicles during wartime. Vehicle maintenance scheduling has an important effect on the recovery of military combat effectiveness. The existing maintenance scheduling methods mainly focus on a single constraint condition for process optimization, which is difficult to meet the actual support requirements. A multi-objective optimization function that integrates multitiple work types and multi-personnel technical level elements is presented according to the size of actual maintenance team, and an improved non-dominated sorting genetic algorithm (NSGA-Ⅱ) based on elitist strategy is established by taking the single process man-hours, total man-hours, immediate predecessor activity, and total human resources as the constraint conditions. In the proposed algorithm, a binary tournament selection operator is added based on the traditional non-dominant elite strategy, and the crossover operator for the multi-objective function optimization is redesigned, and the double coding is used to calculate and solve the preemptive maintenance process scheduling mode. The simulation verification with actual maintenance cases shows that the proposed method is used to reduce the maintenance time and achieves the goal of optimizing the efficiency of human resource scheduling under the conditions of meeting the optimization of complex objectives in wartime.

Key words: vehiclemaintenance, limitedresource, one-timepreemption, processscheduling, activity-list-basedcoding, multi-objective, non-dominatedsortinggeneticalgorithm

CLC Number:

E92
TJ810.7

TANG Runzhi, BAN Liming, QIAN Le, LEI Zhengjun, SONG Weixing. Optimization of Vehicle Maintenance Process Scheduling under Limited Resources[J]. Acta Armamentarii, 2021, 42(9): 2032-2039.

References

［1］马绍民.综合保障工程［M］.北京：国防工业出版社,1995.
MA S M.Comprehensive support project［M］.Beijing:National Defense Industry Press,1995.（in Chinese）
［2］王涛.基于混合进化算法的军用车辆维修保障资源调度优化研究［D］.北京：北京理工大学，2013.
WANG T.Research on maintenance resource scheduling optimization for military vehicles based on hybrid evolutionary algorithm［D］.Beijing:Beijing Institute of Technology,2013.（in Chinese）
［3］ SORL P L.Planificación de proyectos en diagramas de precedencias［D］.València, Spain:en la Universitat de València,1997.
［4］赖昌涛.抢占式资源受限项目调度问题的多Agent优化方法［D］.杭州：浙江大学，2011.
LAI C T.Multi-agent optimization method for preemptive resource-constrained project scheduling problem［D］.Hangzhou:Zhejiang University,2011.（in Chinese）
［5］寿涌毅,彭晓峰,李菲,等.抢占式资源受限项目调度问题的遗传算法［J］.浙江大学学报(工学版),2014, 48(8):1473-1480.
SHOU Y Y,PENG X F,LI F, et al.Genetic algorithms for the preemptive resource-constrained project scheduling problem［J］.Journal of Zhejiang University(Engineering Science),2014,48(8):1473-1480.(in Chinese)
［6］祝政,胡志华.多次抢占项目调度问题的混合遗传算法［J］.计算机工程与应用,2019,55(6):225-230.
ZHU Z,HU Z H.Hybrid genetic algorithm for multiple preemptive project scheduling problem［J］.Computer Engineering and Applications,2019,55(6):225-230.(in Chinese)
［7］ CHEN R M,WU C L,WANG C M, et al.Using novel particle swarm optimization scheme to solve resource-constrained scheduling problem in PSPLIB［J］.Expert Systems with Applications,2010,37(3):1899-1910.
［8］ CHEN R M.Particle swarm optimization with justification and designed mechanisms for resource-constrained project scheduling problem［J］.Expert Systems with Applications,2011,38(6):7102-7111.
［9］ FAHMY A,HASSAN T M,BASSIONI H.Improving RCPSP solutions quality with stacking justification-application with particle swarm optimization［J］.Expert Systems with Applications,2014,41(13):5870-5881.
［10］ JIA Q,SEO Y.An improved particle swarm optimization for the resource-constrained project scheduling problem［J］.The International Journal of Advanced Manufacturing Technology,2013,67(9/ 10/11/12):2627-2638.
［11］ ZHANG H,LI X D,LI H,et al.Particle swarm optimization-based schemes for resource-constrained project scheduling［J］.Automation in Construction, 2005,14(3):393-404.
［12］ HARTMANN S，KOLISCH R.Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem［J］. European Journal of Operational Research,2000, 127(2):394-407.
［13］段鹏飞,余杰,聂慧,等.求解广义优先关系下多技能人员项目调度问题的改进布谷鸟搜索算法［J］.计算机应用研究,2018,35(5):1315-1319.
DUAN P F,YU J,NIE H,et al.Improved cuckoo search algorithm for multi-skilled resource constrained project scheduling problems with generalized precedence relations［J］.Application Research of Computers, 2018,35(5):1315-1319.(in Chinese)
［14］ HAO X X,LIU J,YUAN X X,et al.A moving block sequence-based evolutionary algorithm for resource-constrained project scheduling problems［J］.International Journal of Bio-Inspired Computation,2019,14(2):85-102.
［15］ MA Z Q,HE Z W,WANG N M,et al.A genetic algorithm for the proactive resource-constrained project scheduling problem with activity splitting［J］. IEEE Transactions on Engineering Management,2019, 66:459-474.
［16］ DAI H F,CHENG W M,GUO P.An improved tabu search for multi-skill resource-constrained project scheduling problems under step-deterioration［J］.Arabian Journal for Science & Engineering,2018,43:3279-3290.
［17］ BERTHAUT F,PELLERIN R,HAJJI A,et al.A path relinking-based scatter search for the resource-constrained project scheduling problem［J］.International Journal of Project Organisation & Management, 2018, 10(1):1-36.
［18］ MAGHSOUDLOU H,AFSHAR-NADJAF B,NIAKI S.Preemptive multi-skilled resource constrained project scheduling problem with hard/soft interval due dates［J］.RAIRO Operations Research,2019,53(5):1877-1898.
［19］陈俊杰，同淑荣，叶正梗，等.资源受限多项目调度问题的两阶段算法［J］.控制与决策，2020，35(8):2013-2020.
CHEN J J,TONG S R,YE Z G，et al.Two-stage algorithm for resource-constrained multi-project scheduling problem［J］.Control and Decision, 2020, 35(8):2013-2020.（in Chinese）
［20］ ROSTAMI S,CREEMERS S,LEUS R.New strategies for stochastic resource-constrained project scheduling［J］.Journal of Sche-duling, 2018,21：349-365.
［21］胡涛,马晨辉,申立群，等.基于蚁群算法的测试任务调度优化方法［J］.兵工学报,2019,40(6):1310-1316.
HU T,MA C H,SHEN L Q,et al.Scheduling optimization of test tasks based on ant colony algorithm［J］.Acta Armamentarii,2019,40(6):1310-1316.（in Chinese）
［22］孙笑,宋卫星,班利明,等.复杂人力资源约束下的抢占式维修工序调度［J/OL］.控制与决策,2021［2021-04-23］.https:∥doi.org/10.13195/j.kzyjc.2020.1250.
SUN X,SONG W X,BAN L M,et al.Preemptive maintenance process scheduling under complex human resource constraints［J］.Control and Decision,2021［2021-04-23］.https:∥doi.org/10.13195/j.kzyjc.2020.1250.（in Chinese）

[1]	LU Yuming, ZHANG Xiangfei, LI Ming, ZHAO Minqing. Robust Optimization Design of Fixture Locating Scheme Based on Constrained Multi-objective Optimization Algorithm [J]. Acta Armamentarii, 2022, 43(3): 686-693.
[2]	HU Jing， ZHAI Jiutong， ZHANG Xinming， LI Hailong， XUN Bo. Structural Optimization Design of Double-decker Ball Bearing Based on Response Surface Methodology [J]. Acta Armamentarii, 2022, 43(3): 694-703.
[3]	NIE Junfeng, CHEN Xingjun, SU Qi. Modeling and Optimization of Weapon-target Assignment for Group Targets Defense Based on NSGA-Ⅲ Algorithm [J]. Acta Armamentarii, 2021, 42(8): 1771-1779.
[4]	FENG Kuikui， ZHANG Faping， WANG Wuhong， ZHANG Wenjie， ZHANG Tianhui. Assembly Process Parameters Optimization of Turbine Engine Rotor System Based on Non-dominated Sorting Genetic Algorithm [J]. Acta Armamentarii, 2021, 42(5): 1092-1100.
[5]	SUN Xiaowang， ZHANG Jincheng， PENG Bing， ZHANG Jinkun， WANG Xianhui. Design and Optimization of Occupant Lower Limb Protection Device against Explosion Shock below Military Vehicle [J]. Acta Armamentarii, 2021, 42(12): 2555-2564.
[6]	QIAN Long， CHANG Sijiang， NI Yi. Multi-objective Optimization of Aerodynamic Shape of Microspoiler for Spin-stabilized Projectile [J]. Acta Armamentarii, 2021, 42(12): 2575-2585.
[7]	ZHANG Cheng， LIU Zhaoyang， GU Keqiu. Buffering Mechanism and Characteristic Optimization of Ultra-light Artillery Backtrail [J]. Acta Armamentarii, 2020, 41(9): 1752-1761.
[8]	L Guojun， CAO Jianjun， ZHENG Qibin， CHANG Chen， WENG Nianfeng， PENG Cong. Detection of Similar Duplicate Records Based on OCSVM and Multi-objective Ant Colony Optimization [J]. Acta Armamentarii, 2020, 41(2): 324-331.
[9]	WANG Yadong， SHI Quan， YOU Zhifeng， WANG Fang， XIA Wei. Spare Parts Supply Optimization and Decision-making Based on Cross-efficiency Multi-objective Sorting Evolutionary Algorithm [J]. Acta Armamentarii, 2020, 41(11): 2338-2346.
[10]	ZHANG Fuyi, WU Qin, ZHAO Xiaoyang, LIU Ying, WANG Guoyu. Multi-objective Optimization of Inlet Duct of Water-jet Propulsion Based on Response Surface Method [J]. Acta Armamentarii, 2020, 41(10): 2071-2080.
[11]	WANG Yadong, SHI Quan, CHEN Cai, YOU Zhifeng. Location-allocation Joint Optimization Model of Spare Parts Supply under Supply Disruption Risk [J]. Acta Armamentarii, 2019, 40(8): 1708-1715.
[12]	LUO Qingguo, ZHAO Yao, GUI Yong, LIU Hongbin , SHUAI Gang. Research on Optimization of Louvered Fin with Hybrid Multi-objective Optimizations Based on EDA and AIS [J]. Acta Armamentarii, 2019, 40(4): 689-696.
[13]	LIU Yan, CHEN Chunliang, ZAN Xiang, CHEN Weilong, ZHANG Lijun. Multi-objective Dynamic Scheduling with Accompanying Repair Tasks under Complex Constraints [J]. Acta Armamentarii, 2019, 40(3): 621-628.
[14]	CAI Guangbin, ZHAO Yang, ZHANG Shengxiu, YANG Xiaogang. Robust Multi-objective Linear Parameter-varying Control for Hypersonic Vehicle [J]. Acta Armamentarii, 2019, 40(11): 2229-2240.
[15]	XU Gong-guo , DUAN Xiu-sheng, SHAN Gan-lin, TONG Jun. Optimization Deployment of Multi-sensors in Complex Terrain Based on Multi-objective LM-AQPSO Algorithm [J]. Acta Armamentarii, 2018, 39(11): 2192-2201.