摘要
本研究针对果蔬类自动化立体仓库的存储货位,遵循果蔬类产品的生物特性,结合货物的出入库频率、货架重心、货架安全性等多种存储原则,建立多目标的货位优化数学模型。利用权重法和遗传算法,对构建的模型进行求解,并以某小型果蔬类自动化立体仓库为例进行Matlab仿真验证。结果表明:采用本研究货位优化模型的仓库,货位作业机械运行路程由755.5m降至500.5m,运行时间由14.1min降至9.4min,货物的重量与其所在层的乘积之和由19350个单位降至10913个单位,货物的总质量的差距由18090个单位下降至8067个单位。说明该货位优化模型能够高效地完成货位的分配任务,实现仓库的节能,提高仓库的运行效率和安全性。
Aimed at the storage location of automated three-dimensional warehouse for fruits and vegetables,followed the biological characteristics of fruits and vegetables products, and a multi-objective slotting optimization mathematical model was established in combination with various storage principles such as storage frequency of goods in and out, shelf center of gravity, shelf safety and so on. The weight method and genetic algorithm were used to solve the model. Taking a small automated three-dimensional warehouse for fruits and vegetables as an example,Matlab simulation verification was carried out. The results showed that the running distance of cargo space operation machinery was reduced from 755.5 m to 500.5 m, the running time was reduced from 14.1 min to 9.4 min, the sum of the product of the weight of goods and its layer was reduced from 19350 units to 10913 units, and the difference in the total quality of goods was reduced from 18090 units to 8067 units. That is, the slotting optimization model can efficiently complete the location allocation task, realize the energy saving of the warehouse, and improve the operation efficiency and safety of the warehouse.
作者
李宏峰
余晓晨
许路
LI Hong-feng;YU Xiao-chen;XU Lu(School of Mechanical and Electrical Engineering,Beijing Institute of Graphic Communication,Beijing 102600,China)
出处
《数字印刷》
CAS
北大核心
2022年第1期69-76,共8页
Digital Printing
基金
北京市教委科研计划项目(No.KM201810015006)
北京印刷学院基础研究重点项目(No.Ea201807)。
关键词
果蔬类
自动化仓库
遗传算法
货位优化
Fruits and vegetables
Automated warehouse
Genetic algorithm
Slotting optimization
