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机构地区:[1]上海海事大学物流工程学院,上海201306 [2]上海振华重工电气有限公司软件自动化部,上海200125
出 处:《上海海事大学学报》2017年第3期52-60,共9页Journal of Shanghai Maritime University
基 金:上海海事大学研究生创新基金(2016ycx039)
摘 要:为深入研究新工艺带来的自动化码头设备集成调度问题,针对自动化码头的一种自带提升功能的自动导引小车(L-AGV)和缓冲支架系统,提出新的设备集成调度框架。考虑不同设备之间的相互关联和制约的协同关系,将岸桥分配调度与L-AGV、场桥调度分开,合理定义两种任务(两个问题)的划分方式,建立两个多目标混合整数规划模型。设计一种具有内外层关联的适应度函数的双层遗传算法。相对传统联合调度算法,该算法平衡了计算复杂性与调度均衡性。最后的数值试验证明了模型和算法的有效性。从岸桥数量、任务规模、AGV数量和调度策略等对岸桥等待时间的影响上,对采用L-AGV的系统和采用传统AGV的系统进行比较,为自动化码头装卸作业调度提供决策支持。In order to further study the issue of integrated equipment scheduling caused by new techniques in automated terminals for automated guided vehicles with lifting platforms( called L-AGV) and buffer support system in automated terminal,a new integrated scheduling framework is proposed. Considering the interrelated and constrained cooperativeness relations among different equipments,it is divided into two problems,the quay crane allocation/scheduling problem and the L-AGV and yard crane scheduling problem. By reasonably defining the division of two tasks( two problems),two multi-objective mixed-integer programming models are established sequentially. A two-layer genetic algorithm is developed,where a fitness function is proposed to interlink two layers. The algorithm leads to the tradeoff between the computational complexity and the scheduling equilibrium compared with traditional joint sched-uling algorithms. A numerical test is carried out in order to evaluate the performance of the model and algorithm. The system adopting L-AGVs is compared with the system adopting traditional AGVs through investigating the influence of the number of quay cranes,the scale of tasks and the number scheduling strategies of AGVs on the waiting time of quay cranes. The results provide decision support for automated terminal handling operations.
关 键 词:自动化码头 自动导引小车(AGV) 集成调度 遗传算法(GA) 启发式策略
分 类 号:U691.3[交通运输工程—港口、海岸及近海工程]
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