摘要
针对自动化码头自动导引车(automated guided vehicle,AGV)在作业调度中的充电问题,以最小化所有任务完成时间为目标,建立考虑充电策略的AGV调度模型。对比求解器(Gurobi)与遗传算法的算例求解结果,验证遗传算法的高效性。设计4种充电方式并对其优劣性进行对比,分析AGV数量和续航能力对作业时间和充电利用率的影响。得出结论:按需充电的方式可以有效减少不必要的充电时间,合理的AGV数量配置可以有效提高作业效率和充电利用率。
For the charging issue of automated guided vehicles(AGVs)in operation scheduling of automated terminals,aiming at minimizing the completion time of all tasks,an AGV scheduling model considering charging strategy is established.The results of the solver(Gurobi)and the genetic algorithm are compared through examples,and the efficiency of the genetic algorithm is verified.The four charging schemes are designed,and their advantages and disadvantages are compared.The influence of the number of AGV and the endurance on the working time and the charging utilization rate is analyzed.It is concluded that the on-demand charging scheme can effectively reduce the excess charging time,and the appropriate AGV quantity configuration can effectively improve the operation efficiency and the charging utilization rate.
作者
陈珲
韩晓龙
CHEN Hui;HAN Xiaolong(Institute of Logistics Science&Engineering,Shanghai Maritime University,Shanghai 201306,China)
出处
《上海海事大学学报》
北大核心
2021年第2期20-25,74,共7页
Journal of Shanghai Maritime University
基金
上海市科学技术委员会工程中心能力提升项目(14DZ2280200)。
关键词
自动化码头
自动导引车(AGV)调度
充电策略
遗传算法
automated terminal
automated guided vehicle(AGV)scheduling
charging strategy
genetic algorithm
