Sequence Optimization of Loading/Unloading and Its Automatic Generation Technique for Smart Crane

doi:10.3901/JME.2020.18.254

Abstract

Abstract: Sequence optimization of loading/unloading is a key technique for crane to realize the automatic and smart operation, and improve the operation efficiency. The analysis model of conveyance operation of crane is constructed, and the operation environment and cargo states are defined. Furthermore the cargo position information database is built. The problem of loading and unloading sequence of crane is formulated, and a new search and optimization method is suggested by limiting the number of searching objects in the calculation of the minimum conveyance distance according to the practical operation of crane. Consequently, an effective generation rule, optimization method, and automatic generation technique of loading/unloading sequence for crane are proposed. The effectiveness of the suggested method is validated by numerical simulation. The results show that the suggested method can automatically and rapidly generate the cargo handling sequence, thus the effective and continuous conveyance of large scale cargo can be realized. The suggested method provides technique support for crane to achieve smart operation.

Key words: crane, cargo handling, position information, conveyance sequence

CLC Number:

TH21

LI Guojie, DING Xiaohong. Sequence Optimization of Loading/Unloading and Its Automatic Generation Technique for Smart Crane[J]. Journal of Mechanical Engineering, 2020, 56(18): 254-264.

References

[1] CHEN L,BOSTEL N,DEJAX P,et a1. A tabu search algorithm for the integrated scheduling problem of container handling systems in amaritime terminal[J]. European Joumal of Operational Research,2008,181(1):40-58.
[2] UNSAL O,OGUZ C. Constraint programming approach to quay crane scheduling problem[J]. Transportation Research Part E,2013,59:108-122.
[3] CHEN J H,LI D H,GOH M. An efective mathematical formulation for the unidirectional cluster-based quay crane scheduling problem[J]. European Journal of Operational Research,2014,232(1):198-208.
[4] 梁承姬,沈佳杰. 考虑装卸顺序的岸桥与集卡协调调度问题研究[J]. 计算机应用研究,2016,33(12):3591-3595. LIANG Chengji,SHEN Jiajie. Study on problem of quay cranes and container trucks scheduling with consideration of handling order[J]. Application Research of Computers,2016,33(12):3591-3595.
[5] 秦天保,葛浩,沙梅. 约束规划求解集装箱装卸系统集成调度问题[J]. 系统工程理论与实践,2015,35(8):2127-2136. QIN Tianbao,GE Hao,SHA Mei. Constraint program m ing for the integrated scheduling problem of container handling systems in container terminals[J]. Systems Engineering:Theory & Practice,2015,35(8):2127-2136.
[6] 张睿,靳志宏,邢曦文,等. 同贝同步模式下的集装箱装卸作业调度优化[J]. 系统工程学报,2014,29(6):833-844. ZHANG Rui,JIN Zhihong,XING Xiwen,et al. Optimization of container scheduling on integrated loading and unloading operations in same ship-bay[J]. Journal of Systems Engineering,2014,29(6):833-844.
[7] 梁亮,陆志强. 集装箱码头装卸系统集成调度的建模与优化[J]. 系统工程理论与实践,2010,30(3):476-483. LIANG Liang,LU Zhiqiang. Modeling and optimization of the integrated scheduling problem of container handling system[J]. Systems Engineering:Theory & Practice,2010,30(3):476-483.
[8] 曾庆成,杨忠振. 集装箱码头集成调度模型与混合优化算法[J]. 系统工程学报,2010,25(2):264-270. ZENG Qingcheng,YANG Zhongzhen. Integrating scheduling model and hybrid optimization algorithm for container terminals[J]. Journal of Systems Engineering,2010,25(2):264-270.
[9] 张文霞. 遗传算法在港口集装箱装卸顺序中的应用[J]. 舰船科学技术,2017,39(1A):144-146. ZHANG Wenxia. Genetic algorithm in the application of the port container loading and unloading of the order[J]. Ship Science and Technology,2017,39(1A):144-146.
[10] 张维英,林焰,纪卓尚,等. 出口集装箱堆场取箱作业优化模型研究[J]. 武汉理工大学学报,2006,30(2):314-317. ZHANG Weiying,LIN Yan,JI Zhuoshang,et al. Optimization model of containers loading operation in export containers terminal[J]. Journal of Wuhan University of Technology,2006,30(2):314-317.
[11] 贾庆轩,陈钢,孙汉旭,等. 基于A*算法的空间机械臂避障路径规划[J]. 机械工程学报,2010,46(13):109-115. JIA Qingxuan,CHEN Gang,SUN Hanxu,et al. Path planning for space manipulator to avoid obstacle based on A* algorithm[J]. Journal of Mechanical Engineering,2010,46(13):109-115.
[12] 史也,梁斌,王学谦,等. 基于量子粒子群优化算法的空间机器人非完整笛卡尔路径规划[J]. 机械工程学报,2011,47(23):65-73. SHI Ye,LIANG Bin,WANG Xueqian,et al. Cartesian non-holonomic path planning of space robot based on quantum-behaved particle swarm optimization algorithm[J]. Journal of Mechanical Engineering,2011,47(23):65-73.
[13] 汪首坤,郭俊杰,王军政,等. 基于混合群智能优化的机器人立体视觉标定[J]. 机械工程学报,2012,48(1):57-63. WANG Shoukun,GUO Junjie,WANG Junzheng,et al. Robot stereo vision calibration based on hybrid swarm intelligent optimization[J]. Journal of Mechanical Engineering,2012,48(1):57-63.
[14] 季旭全,王君臣,赵江地,等. 基于机器人与视觉引导的星载设备智能装配方法[J]. 机械工程学报,2018,54(23):63-72. JI Xuquan,WANG Junchen,ZHAO Jiangdi,et al. Intemgent robotic assembly method of spaceborne equipment based on visual guidance[J]. Journal of Mechanical Engineering,2018,54(23):63-72.
[15] 李运华,何刘宇,杨丽曼. 非完整约束多轴驱动车辆的路径跟踪控制[J]. 机械工程学报,2014,50(5):33-41. LI Yunhua,HE Liuyu,YANG Liman. Path-following control of nonholonomic constraint multi-axle drive vbhicle[J]. Journal of Mechanical Engineering,2014,50(5):33-41.
[16] 王艺,蔡英凤,陈龙,等. 基于模型预测控制的智能网联汽车路径跟踪控制器设计[J]. 机械工程学报,2019,55(8):136-144. WANG Yi,CAI Yingfeng,CHEN Long,et al. Design of intelligent and connected vehicle path tracking controller based on model predictive control[J]. Journal of Mechanical Engineering,2019,55(8):136-144.
[17] 牛礼民,杨洪源,周亚洲,等. 混合动力汽车动力总成多智能体集成控制策略[J]. 机械工程学报,2019,55(12):168-188. NIU Limin,YANG Hongyuan,ZHOU Yazhou,et al. Hybrid electric vehicle integrated control strategy based on multi-agent[J]. Journal of Mechanical Engineering,2019,55(12):168-188.
[18] 张永祥,刘心,褚志刚,等. 基于随机子空间法的模态参数自动提取[J]. 机械工程学报,2018,54(9):187-194. ZHANG Yongxiang,LIU Xin,CHU Zhigang,et al. Autonomous modal parameter extraction based on stochastic subspace identification[J]. Journal of Mechanical Engineering,2018,54(9):187-194.
[19] 马江涛,刘检华,徐联杰,等. 基于LTL-PRM算法的分支管路自动布局方法[J]. 机械工程学报,2018,54(15):160-170. MA Jiangtao,LIU Jianhua,XU Lianjie,et al. Method of automatic branch-pipe routing based LTL-PRM algorithm[J]. Journal of Mechanical Engineering,2018,54(15):160-170.