Travel time and alternative configurations analysis for automated storage/retrieval systems based on geometrical method

In order to evaluate the efficiency of the automated storage/retrieval system(AS/RS)accurately,and compare different layouts of the AS/RS using mean travel time,under randomized storage conditions,an exact,geometry-based analytical model is presented.The model can be used to compute the expected single-command and dual-command travel time for a storage/retrieval(S/R)machine which can travel simultaneously horizontally and vertically as it moves along a storage aisle.The rack may be either square in time or non square in time.Additionally,the alternative layouts of the AS/RS and travel-time models are examined.Comparing with setting the I/O point at the left-lower corner of the rack,setting the I/O point at any point at the vertical edge can help enhance the efficiency of the AS/RS.

A Multi-stage Heuristic Algorithm for Matching Problem in the Modified Miniload Automated Storage and Retrieval System of E-commerce

E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.

The Complexity and On-Line Algorithm for Automated Storage and Retrieval System with Stacker Cranes on One Rail

This paper considers an on-line scheduling and routing problem concerning the automated storage and retrieval system from tobacco industry. In this problem, stacker cranes run on one common rail between two racks. Multiple input/output-points are located at the bottom of the racks. The stacker cranes transport bins between the input/output-points and cells on the racks to complete requests generated over time. Each request should be accomplished within its response time. The objective is to minimize the time by which all the generated requests are completed. Under a given physical layout, the authors study the complexity of the problem and design on-line algorithms for both one-stacker-crane model and two-stacker-crane model. The algorithms axe validated by instances and numerical simulations.

自动化立体仓库退库货位优化问题及其求解算法

针对自动化立体仓库出库作业过程中剩余货物退库问题,以堆垛机作业总能耗最小化为目标,以退库货位分配为决策变量,建立了自动化立体仓库退库货位优化模型,提出了基于深度强化学习的自动化立体仓库退库货位优化框架。在该框架内,以立体仓库实时存储信息和出库作业信息构建多维状态,以退库货位选择构建动作,建立自动化立体仓库退库货位优化的马尔科夫决策过程模型;将立体仓库多维状态特征输入双层决斗网络,采用决斗双重深度Q网络(dueling double deep Q-network,D3QN)算法训练网络模型并预测退库动作目标价值,以确定智能体的最优行为策略。实验结果表明D3QN算法在求解大规模退库货位优化问题上具有较好的稳定性。

随机订单驱动的集中式和分散式AS/RS建模及仿真

为了分析集中式和分散式自动存取系统与订单结构的适配性,在同时满足作业类型随机、订单时间随机和品规随机(作业储位随机)的条件下,通过分析设备运动轨迹、设备运动时间模型、作业时间构成及多作业间的时序关系,为两种系统建立作业时间模型;调整货架结构和订单密度两个参数,借助MATLAB仿真,研究货架结构和订单密度与两系统的适配性;构建作业效率和成本的系统评价多目标模型,并求得非劣解;结果表明,货架列数增加越多,分散式系统的并行作业效益越明显;随着订单密度的降低,分散式系统的并行作业效益也逐渐减弱;在长方形货架、订单密度较高情况下,分散式系统优于集中式系统;当考虑效率和成本双因素评价时,货架列数为100,层数为9层的分散式系统的优势最明显。

AVS/RS系统冲突与死锁控制策略

针对多小车多升降机自动小车存取系统的安全性需求,提出一种基于迭代时间窗的系统冲突与死锁控制策略。通过改进的Banker算法分别完成小车2个作业阶段的最短路径检测,同时对系统冲突与死锁类型进行了分类,给出了基于迭代时间窗法的冲突与死锁控制策略,并通过具体实例进行详细验证。结果表明,该文提出的系统冲突及死锁控制策略,能够在提高小车运行效率的同时,增强系统的安全性能。

AS/RS在图书馆中的应用——以加州州立大学北岭校区Oviatt图书馆为例

馆藏空间永远是图书馆关注的核心问题。各大图书馆在面临空间不足时采取着不同的策略,包括建立保存与管理制度、合作典藏、纸本淘汰政策、馆藏数字化与网络电子资源、密集书库等。作为高密度自动化存取的代表,自动化立体仓库能够极大地节省空间,实现快速存取,近几年在图书馆领域呈现出快速增长的态势。本文以加州州立大学北岭校区Oviatt图书馆为例,介绍自动化立体仓库在图书馆中的应用。

SP-AS/RS基于新型出入口结构的行程时间分析

为建立分离平台式自动化存储系统的双命令行程时间分析模型,寻求自动化存储系统的最佳设计,文中引入新型的系统出入口位置结构,通过分析分离平台式自动化存储系统的运作流程,建立双命令周期的行程时间数学模型,并验证模型优化的有效性。从期望行程时间角度分析,当形状因子b=1时,提出的模型有效率更高,提高了27.92%。研究的创新性在于引入新型出入口位置结构之后,用更为实际的双命令存储模式对自动化存储系统进行了行程时间分析,优化了双命令周期期望行程时间模型。在双命令周期存储模式下,分离平台式自动化存储系统引入新型出入口位置结构后,相比传统的分离平台式自动化存储系统的运作效率更高。

烟草行业自动化立体仓库的可视化盘点技术与方法研究

文章结合某烟草企业自动化立体仓库(Automated Storage/Retrieval Systems, AS/RS)存货盘点管理特点和实际需求,建立了一种基于图像回传方法与信息化技术的实施框架。在此基础上,设计了多种存货盘点模式以满足差异化的需求,并予以了实施和应用验证,为烟草行业AS/RS实现安全、高效、柔性和可追溯的存货盘点提供了一个有效的解决方案。最后,对图像自动识别技术在其中的应用进行了算法设计和可行性分析,为提升该行业AS/RS存货盘点的智能化水平提供了参考。

基于深度学习的货物盘点自动识别方法研究

文章针对自动化立体仓库(Automated Storage/Retrieval Systems,AS/RS)在高效及安全库存盘点、货物监控等方面的需求和存在的问题,提出了一种基于YOLOv3深度学习算法的货物异动及数量自动识别方法,并进行了算法实现。为验证该算法的有效性,文章以某烟草物流中心自动化立体仓库为对象进行了应用验证分析,结果表明该算法在经过小规模货物图像样本训练后即具备较高的识别能力,因此,采用该方法进行货物异动监控和数量自动识别具有较高的可行性和有效性。

具有AGV和AS/RS的装配线物流系统分析

阐述了具有自动导引车(AGV)和自动存取系统(AS/RS)的物流系统的工作流程,建立了该类物流系统的排队网络模型,分析了系统的性能与系统设计参数之间的关系,为设计具有AGV和AS/RS的复杂物流系统提供依据。

AS/RS based yard and yard planning

In this paper, we apply the split-platform automated storage/retrieval systems (SP-AS/RSs) (Hu et al., 2005) to store containers in the yard to improve the yard performance and to increase the utilization of the yard space. The layout of an SP-AS/RS based yard is described in detail. To achieve an efficient operation, we present a novel yard space allocation policy called the ‘second-carrier-based allocation policy’, which can help to alleviate the out-of-sequence problem of containers and the congestion of vehicles at the AS/RS racks. Different allocation policies are compared by an integrated container terminal simulation system. The simulation results show that the second-carrier-based policy is very efficient and has the potential to offer high terminal performance.

Optimization of Operational Route in AS/RS Based on Particle Swarm Algorithm

Optimization of the operational route in the automated storage/retrieval system （AS/RS） is transformed into the traveling salesman problem, To make the moving distance of the storage/retrieval machine shortest, we carry out a group of tests where 20 goods locations are chosed. Using PSO for operational route of AS/RS, the operation time can be shortened by about 11%. The experiments indicate that under the same conditions, the more the goods locations are, the higher the operation efficiency of the storage/retrieval machine is.

Scheduling Storage Process of Shuttle-Based Storage and Retrieval Systems Based on Reinforcement Learning

The Shuttle-Based Storage and Retrieval System(SBS/RS)has been widely studied because it is currently the most efficient automated warehousing system.Most of the related existing studies are focused on the prediction and improvement of the efficiency of such a system at the design stage.Hence,the control of existing SBS/RSs has been rarely investigated.In existing SBS/RSs,some empirical rules,such as storing loads column by column,are used to control or schedule the storage process.The question is whether or not the control of the storage process in an existing system can be improved further by using a different approach.The storage process is controlled to minimize the makespan of storing a series of loads into racks.Empirical storage rules are easy to control,but they do not reach the minimum makespan.In this study,the performance of a control system that uses reinforcement learning to schedule the storage process of an SBS/RS with fixed configurations is evaluated.Specifically,a reinforcement learning algorithm called the actor-critic algorithm is used.This algorithm is made up of two neural networks and is effective in making decisions and updating itself.It can also reduce the makespan relative to the existing empirical rules used to improve system performance.Experiment results show that in an SBS/RS comprising six columns and six tiers and featuring a storage capacity of 72 loads,the actor-critic algorithm can reduce the makespan by 6.67%relative to the column-by-column storage rule.The proposed algorithm also reduces the makespan by more than 30%when the number of loads being stored is in the range of 7–45,which is equal to 9.7%–62.5%of the systems’storage capacity.

面向管材存储的自动化立体仓库货位优化

文章以自动化立体仓库(automated storage and retrieval system,AS/RS)中管材的货位分配为研究对象,采用悬臂式货架进行存储,以存取效率、货架稳定性和货架平衡性为原则,建立多目标货位优化模型;设计粒子群算法(particle swarm optimization,PSO)和遗传算法(genetic algorithm,GA)的混合算法求解模型,使用MATLAB编程并运行汽车制管厂的实例数据进行仿真分析。结果表明,该文方法相较于传统PSO算法和GA算法具有一定的优越性,能够有效提高AS/RS的作业效率和货架安全性,对面向管材存储的AS/RS研究具有一定的理论和实践意义。

基于遗传算法的自动化立体仓库货位优化研究

文章针对单元货格式自动化立体仓库最为核心的货位优化问题,提出以出入库效率、货架稳定性以及工作量均衡为目标的优化模型,对建立的多目标数学模型,利用权重法转化为单目标优化问题,再用遗传算法对该问题进行求解,并以某食品生产企业M公司所建立体仓库的真实数据为例,最后在Matlab中使用遗传算法进行仿真验证。结果表明该模型对于自动化立体仓库的优化效果明显,并且在解决巷道工作量均衡问题方面对于不同类型的立体仓库具有一定的普适性。

自动化立体仓库中环形2-RGV系统入库调度模型与求解算法

确定合理的货物运送序列,实现穿梭车(RGV)与堆垛机协同作业是提升自动化立体仓库中环形2-RGV系统搬运效率的重要手段。通过对RGV在环形轨道运作环境下的碰撞情况进行分析,以货物总入库时间最小化为目标,考虑了同一辆RGV运送、两RGV碰撞避免以及RGV与堆垛机协同运作等约束,构建了环形2-RGV系统入库调度问题的混合整数规划模型,设计了可快速求解问题的混合变邻域禁忌搜索(HVNTS)算法。为验证算法的有效性,设计了25组不同规模的算例,并将HVNTS算法的求解结果与CPLEX和禁忌搜索算法的求解结果相比较,算例实验结果表明:货物的平均入库时间分别节省了0.36%和8.67%,且HVNTS算法的求解时间均在3 min内,证明所提算法能快速有效地求解该问题。

基于西门子PLC的自动化立体仓库系统设计与仿真

为顺应仓储行业不断发展的趋势,改进以数量、规模、人力为依托的粗放型仓库管理模式,提高生产效率,克服人员疏忽等问题,采用西门子1200系列PLC设计一款自动化立体仓库系统。设计以实际工业生产中高安全与高效率的要求为考量,在系统硬件和程序设计时采取多种措施保证系统安全性与运行效率,同时能够有效实现物料自动分类存放、自动出库以及仓库存储状态实时显示等功能。在虚拟仿真软件Factory I/O中搭建系统硬件模型对功能进行验证,结果表明,所设计自动化立体仓库系统性能良好,操作简单,功能完善,可满足大多数仓储企业的业务需求。

自动化控制系统中通信协议设计研究

讨论了自动化系统中计算机控制与下位控制器之间进行通信的协议设计问题。重点说明了采用集成设计的思想,对自动化立体PLC仓库管理和控制软件系统全盘考虑的构思下通信协议的设计。采用这种集成思想所设计的通信程序,其协议简明,对传输媒介要求低,并具有对通信过程的监控功能,既能适合点到点的网络结构又适用于总线式网络结构。

基于遗传算法的立体仓库堆垛机路径优化

目的提出一种基于遗传算法的立体仓库堆垛机路径优化方法,研究对固定货架子系统堆垛机拣选作业优化调度问题.方法分段分析设计遗传算法中适应度函数,在消息任务队列中,为了避免个别任务等待时间过长,在数学模型中加入任务的等待时间.运用遗传算法具有快速全局搜索能力,求解速度快等特点,优化自动化立体仓库堆垛机拣选作业运行路径.结果分段分析设计适应度函数避免了在遗传算法早期出现个别特殊个体,等待时间参数改善了个别任务等待时间过长的现象,更符合工程实际要求.结论实验仿真和工程实际应用都证明该算法可以有效地减少堆垛机系统拣选作业运行时间,提高了立体仓库的作业效率.表明了遗传算法在仓库任务调度应用上的可行性和有效性,为实际生产提供了理论依据.