飞机移动生产线物料配送与空箱回收集成建模
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摘要
为了解决飞机移动生产线中作业物料的供给问题,构建了飞机移动生产线物料配送与空箱回收集成决策的模型并设计了求解算法.在物料组批和小车调度的基础上,引入了空箱的回收决策,建立了以小车出行次数最小化为目标的数学模型并设计了一种以遗传算法为框架的启发式算法.在遗传算法较优的全局搜索能力下,综合考虑小车的运载能力与线边空间的存储能力,设计了启发式算法对物料与空箱的组批方式以及小车出行时刻三类变量联合进行决策,并结合了局部搜索算法进行再优化.对提出的算法进行了数值实验,实验结果证明了模型与算法的有效性.
To solve the material supply problem for aircraft moving assembly line,an integrated model was formulated to make decisions of material delivery and container pickup,and the scheduling method was proposed to solve the model.On the basis of the material-batching and vehicle scheduling problems,decisions on the pickup of line-side containers were introduced.An integrating mathematical model with the objective of minimizing the number of deliveries was established and a heuristic algorithm based on genetic algorithm was proposed.Due to the global searching advantage of genetic algorithm,an improved heuristic algorithm was introduced to make a joint decision on three variables of the batching of job's material and container,and delivery time,which took into account of the capacity of the delivery and line-side storage,and combined with the local search algorithm for reoptimization.Results of the numerical experiments proved the model and algorithms.
To solve the material supply problem for aircraft moving assembly line,an integrated model was formulated to make decisions of material delivery and container pickup,and the scheduling method was proposed to solve the model.On the basis of the material-batching and vehicle scheduling problems,decisions on the pickup of line-side containers were introduced.An integrating mathematical model with the objective of minimizing the number of deliveries was established and a heuristic algorithm based on genetic algorithm was proposed.Due to the global searching advantage of genetic algorithm,an improved heuristic algorithm was introduced to make a joint decision on three variables of the batching of job's material and container,and delivery time,which took into account of the capacity of the delivery and line-side storage,and combined with the local search algorithm for reoptimization.Results of the numerical experiments proved the model and algorithms.
引文
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[2]MEI Z,LIU Y,YOUNUS M.Material delivery system for aircraft composite component manufacturing workshop[C]//Proceedings of the International Multi Conference of Engineers and Computer Scientists.Hong Kong:[s.n.],2011:1097-1102.
[3]BOYSEN N,EMDE S,HOECK M,et al.Part logistics in the automotive industry:decision problems,literature review and research agenda[J].European Journal of Operational Research,2015,242(1):107.
[4]SOUZA M C,CARVALHO C R V,Brizon W B.Packing items to feed assembly lines[J].European Journal of Operational Research,2008,184(2):480.
[5]CUNHA A S,SOUZA M C.Stronger upper and lower bounds for a hard batching problem to feed assembly lines[J].Electronic Notes in Discrete Mathematics,2008,30:159.
[6]EMDE S,GENDREAU M.Scheduling in-house transport vehicles to feed parts to automotive assembly lines[J].European Journal of Operational Research,2017,260(1):255.
[7]BOYSEN N,BRISKORN D,EMDE S.Just-in-time vehicle scheduling with capacity constraints[J].IIE Transactions,2016,48(2):134.
[8]GOLZ J,GUJJULA R,GNTHER H O,et al.Part feeding at high-variant mixed-model assembly lines[J].Flexible Services and Manufacturing Journal,2012,24(2):119.
[9]FATHI M,ALVAREZ M J,MEHRABAN F H,et al.Amultiobjective optimization algorithm to solve the part feeding problem in mixed-model assembly lines[J].Mathematical Problems in Engineering,2014,11(1):809.
[10]胡鑫铭,陆志强.飞机移动生产线物料配送与线边存储集成优化[J].工程科学学报,2018,40(1):108.HU Xinming,LU Zhiqiang.Integrated optimization of material delivery and line-side storage problem for aircraft moving assembly line[J].Chinese Journal of Engineering,2018,40(1):108.
[11]朱永国,李俊杰,刘春锋,等.基于正态模糊时间窗约束的飞机装配物料配送路径规划[J].中国机械工程,2017,28(21):2534.ZHU Yongguo,LI Junjie,LIU Chunfeng,et al.Aircraft assembly material delivery path planning based on normal fuzzy time window constraints[J].China Mechanical Engineering,2017,28(21):2534.
[12]LI H,DEMEULEMEESTER E.A genetic algorithm for the robust resource leveling problem[J].Journal of Scheduling,2016,19(1):43.
[13]BENNELL J A,LEE L S,POTTS C N.A genetic algorithm for two-dimensional bin packing with due dates[J].International Journal of Production Economics,2013,145(2):547.
[14]LIN Y K,CHONG C S.Fast GA-based project scheduling for computing resources allocation in a cloud manufacturing system[J].Journal of Intelligent Manufacturing,2017,28(5):1.
[15]FLESZAR K,CHARALAMBOUS C.Average-weightcontrolled bin-oriented heuristics for the one-dimensional binpacking problem[J].European Journal of Operational Research,2011,210(2):176.