钢铁企业出厂物流集成多目标优化问题
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摘要
针对钢铁企业成品出厂过程中所存在的物流衔接效率低和运输成本高的问题,将装配计划与运输调度进行集成优化,建立了钢铁企业成品出厂物流集成优化问题的多目标混合整数规划模型,根据问题特点提出了一个改进的多目标变邻域搜索算法,在算法中充分考虑了装配计划与运输调度的特点,以实现2个优化子问题之间的集成与协调。基于仿真算例的测试结果验证了所提出算法的有效性。
To handle the low efficiency and high transportation cost of the outbound logistics in iron and steel enterprises, the consolidation planning and transportation scheduling are integrated for optimization. A multi-objective mixed integer programming model is formulated for this problem. According to the characteristics of the problem, a multi-objective variable neighborhood search algorithm is proposed. The characteristics of consolidation planning and transportation scheduling are taken into account so as to achieve the integration and coordination of the two sub-problems. Computational results based on simulated instances illustrate the efficiency of the proposed algorithm.
To handle the low efficiency and high transportation cost of the outbound logistics in iron and steel enterprises, the consolidation planning and transportation scheduling are integrated for optimization. A multi-objective mixed integer programming model is formulated for this problem. According to the characteristics of the problem, a multi-objective variable neighborhood search algorithm is proposed. The characteristics of consolidation planning and transportation scheduling are taken into account so as to achieve the integration and coordination of the two sub-problems. Computational results based on simulated instances illustrate the efficiency of the proposed algorithm.
引文
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[12]李坤,唐立新.集装箱码头装船计划问题建模与优化研究[J].控制工程,2015,22(4):683-689.Li K,Tang L X.Modeling and optimizing for the container stowage planning problem in container terminal[J].Control Engineering of China,2015,22(4):683-689.
[13]Deb K,Agrawal S,Pratap A,et al.A fast and elitist multi-objective genetic algorithm:NSGA-II.IEEE Transactions on Evolutionary Computation,2002,6(2),182-197.
[2]Zapfel G,Wasner M.Warehouse sequencing in the steel supply chain as a generalized job shop model[J].International Journal of Production Economics,2006,104(2):482-501.
[3]Wang GM,Jin C,Deng XY.Modeling and optimization on steel plate pick-up operation scheduling on stackyard of shipyard[C].In proceedings of IEEE International Conference on Automation and Logistics,2008,pp.548-553.
[4]Tang LX,Ren HZ.Modelling and a segmented dynamic programming-based heuristic approach for the slab stack shuffling problem[J].Computers&Operations Research,2010,37(2):368-375.
[5]Shiraishi K,Kimura H.Planning for delivering steel plates in a stockyard using hierarchical reinforcement learning[J].Japanese Naval Architecture and Ocean Engineering Society Proceedings,2011,13(6):165-173.
[6]Zhang ZY,Wang P,Wang WZ.Optimization and operation scheduling for a steel plate yard based on greedy algorithm[J].Journal of Networks,2013,8(7):1654-1659.
[7]Umeda T,Kitamura A,Konishi M,et al.Optimization search algorithm of allocation planning for strip coils in hold for shipment by using operational know-how[J].ISIJ International,2001,41(5):446-453.
[8]Yang F,Tang LX.A scatter search optimization for ship consolidation plan for strip coils to reduce the number of shuffling[C].In proceedings of 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems,2009,367-371.
[9]Yang F,Tang L X,Yuan Y,et al.Mixed integer linear programming and solution for the multi-tank train stowage planning problem of coils in steel industry[J].ISIJ International,2014,54(3):634-643.
[10]Tang L X,Li K.An inherited tabu search algorithm for the truck and trailer vehicle scheduling problem in iron and steel industry[J].ISIJInternational,2009,49(1):51-57.
[11]Cheng Y R,Liang B,Zhou M H.Optimization for vehicle scheduling in iron and steel works based on semi-trailer swap transport[J].Journal of Central South University of Technology,2010,17(4):873-879.
[12]李坤,唐立新.集装箱码头装船计划问题建模与优化研究[J].控制工程,2015,22(4):683-689.Li K,Tang L X.Modeling and optimizing for the container stowage planning problem in container terminal[J].Control Engineering of China,2015,22(4):683-689.
[13]Deb K,Agrawal S,Pratap A,et al.A fast and elitist multi-objective genetic algorithm:NSGA-II.IEEE Transactions on Evolutionary Computation,2002,6(2),182-197.