基于遗传算法的铁路集装箱装卸门吊作业优化研究
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摘要
集装箱装卸门吊作业是铁路集装箱运输的基础,为提高铁路集装箱装卸效率,在分析集装箱运输效率影响因素的基础上,综合考虑集装箱在箱区位置、集装箱在车上预期位置及门吊作业顺序,以装卸作业过程中门吊总运行距离最小为优化目标,基于遗传算法建立铁路集装箱装卸作业优化模型并求解。根据集装箱装卸线门吊作业实例分析,计算结果表明:铁路集装箱装卸门吊作业优化模型能够找到集装箱装卸的最优顺序,可以实现缩短集装箱装卸时间、降低装卸成本的目的,验证了该模型的有效性和合理性。
Loading and unloading operation of containers with gantry cranes is the basis of railway container transportation. To improve efficiency, based on an analysis of the factors affecting the efficiency of container transportation focusing on the location of containers in the container area, the expected position of containers on the vehicle and the sequence of gantry crane operation, this paper has put forward a modal with solution to improve the loading and unloading operation of railway containers aiming at minimizing the total operating distance of gantry cranes based on genetic algorithm. To verify the effectiveness and rationality of the proposed modal, this paper has carried out case studies whose results have shown that the best operation flow can be worked out, which will cut down both operation time and costs.
Loading and unloading operation of containers with gantry cranes is the basis of railway container transportation. To improve efficiency, based on an analysis of the factors affecting the efficiency of container transportation focusing on the location of containers in the container area, the expected position of containers on the vehicle and the sequence of gantry crane operation, this paper has put forward a modal with solution to improve the loading and unloading operation of railway containers aiming at minimizing the total operating distance of gantry cranes based on genetic algorithm. To verify the effectiveness and rationality of the proposed modal, this paper has carried out case studies whose results have shown that the best operation flow can be worked out, which will cut down both operation time and costs.
引文
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[2]许奇,何天健,毛保华.我国铁路集装箱多式联运现状与发展[J].交通运输系统工程与信息,2018,18(6):194-200.XU Qi,HE Tianjian,MAO Baohua.The Development and Current Status of RailwayContainer Intermodal Transport in China[J].Journal of Transportation Systems Engineering and Information Technology,2018,18(6):194-200.
[3]鲁渤,王辉坡,汪寿阳.需求约束下集装箱码头装卸设施配置逆优化模型[J].系统工程学报,2018,33(6):845-853.LU Bo,WANG Huipo,WANG Shouyang.Inverse Optimization Model of Loading and Unloading Facilitiesin Container Terminal under Demand Constraint[J].Journal of Systems Engineering,2018,33(6):845-853.
[4]刘杰,何世伟,郭建民,等.铁路货运产品与车站资源协同分配优化模型及算法研究[J].铁道学报,2017(5):19-25.LIU Jie,HE Shiwei,GUO Jianmin,et al.Optimization Model and Algorithm for Collaborative Assignment between Cargo Products and Station Resources[J].Journal of the China Railway Society,2017(5):19-25.
[5]赵小毓.基于物联网的铁路物流中心集装箱功能区装卸资源调度优化研究[D].北京:北京交通大学,2017.
[6]杨广全,马玉坤,刘飞.基于遗传算法的集装箱装车配载方案的优化[J].中国铁道科学,2014,35(6):124-130.YANG Guangquan,MA Yukun,LIU Fei.GA-based Matching Scheme Optimization for Container Loading onto Railway Vehicle[J].China Railway Science,2014,35(6):124-130.
[7]任洁.基于遗传算法的集装箱码头泊位和岸桥分配问题的研究[D].呼和浩特:内蒙古大学,2017.
[8]杨广全,梁永刚,刘平.基于遗传算法的铁路小型集装箱装车配载优化[J].铁道货运,2017,35(5):41-45.YANG Guangquan,LIANG Yonggang,LIU Ping.Optimal Vehicle Loading of Railway Small Container based on GeneticAlgorithm[J].Railway Freight Transport,2017,35(5):41-45.
[9]WANG L,XIA X H,CAO J H,et al.Improved Ant Colony-Genetic Algorithm for Information Transmission Path Optimization in Remanufacturing Service System[J].Chinese Journal of Mechanical Engineering,2018,31(1):107-119.