改进自适应遗传算法求解“货到人”拣选系统订单分批问题

“货到人”拣选系统采用自动导引运输车(Automated guided vehicle,AGV)实现自动拣选作业,由AGV搬运货架到拣选站台,再由拣选人员从货架上拣取商品。订单分批作为拣选作业的准备工作,是影响AGV搬运次数和人工拣货次数的关键因素,优化订单分批策略对提高“货到人”拣选系统效率至关重要。在电商智能仓库背景下,综合考虑订单需求多种商品、商品多货架分布存储、订单与货架供需匹配关系未知等实际因素,以人工拣选成本和AGV搬运成本之和最小为目标构建数学模型,并设计改进自适应遗传算法求解。该算法采用启发式策略生成初始种群,引入具有自适应变换概率的交叉和变异算子,并加入局部搜索过程以增强寻优能力。最后通过试验测试验证模型和算法的有效性,证明种群初始化方法的优势,并采用灵敏度分析给出合理的周转箱数量配置建议。研究可为电商企业通过订单分批优化提高拣选效率、降低拣选成本提供实践指导,为“货到人”拣选系统的实际应用提供科学依据。     

名优茶采摘机器人的系统设计与试验

针对名优茶采摘劳动力短缺的现状,设计了一种适用于自然环境下作业的名优茶采摘机器人。系统由采摘机械手、3P-Delta机械臂、视觉系统和主控系统构成。机器人通过深度相机获取茶蓬图像,利用深度学习和骨架法计算采摘点。从名优茶的生长特征出发,建立了机械臂采摘轨迹模型,采用Bézier曲线对茶叶采摘路径进行优化,降低了机械臂在快速运动过程中的加速度突变,提高了采摘运动的平滑性。利用虚功原理建立机械臂动力学模型,基于滑模控制设计了机械臂采摘控制策略,优化了控制算法中的指数趋近律,有效地抑制了滑模面在快速趋近时的抖振现象。实地测试结果表明,采摘机器人能够实现名优茶的采摘,采摘率和完整率分别为75.53%和54.68%,平均采摘速度为0.451颗/s。     

自动补货系统补货缓存优化

为提高自动分拣系统作业效率、降低补货设备投入成本,在对自动补货系统中补货缓存作业过程分析的基础上,建立补货缓存设备输入输出平衡模型,提出补货缓存满足分拣作业的最优条件及临界条件;根据自动备货系统与分拣系统之间的布局关系,建立补货缓存中货物到达过程的数学模型和补货缓存长度的优化模型;设计“先聚类,后排序”的启发式聚类方法对备货系统的品项分配进行优化,仿真结果显示,优化后的品项分配与按照总量排序分配方法相比,补货缓存长度减少约9%。     

未知时变环境下采摘机器人电液伺服控制系统

为保证采摘机器人在未知时变环境下的控制稳定性和机器人末端执行器的位置执行精度,优化采摘机器人电液伺服控制系统。系统基于直流电动机驱动机器人各个关节,构建采摘机器人电液伺服控制系统的数学模型;通过加权自扰动递推最小二乘法辨识采摘机器人接触动力学模型实时控制参数后,结合小脑神经网络和PID算法,分别实现前馈控制和反馈控制,以此优化采摘机器人电液伺服控制系统。结果表明：优化后系统具备较好的控制参数辨识效果,机器人末端执行器在3个方向的误差接近于0;可在2 s内完成控制,超调量在2%以内;控制机器人在静态和动态2种状态下,液压缸活塞的位移结果均低于1.6 cm。     

“货到人”拣选系统订单排序优化

"货到人"拣选系统采用"出库-拣选-回库"的拣选模式,货箱出入库频率高成为制约拣选效率的关键。为降低货箱出入库频率,进而提高系统拣选效率,提出订单排序优化模型。定义订单耦合因子表示两个订单之间可放置于拣选缓存中的共用货箱数量,并以此作为模型参数,将优化目标由提高拣选效率转化为降低货箱出入库频率。模型中,每个拣选台内的订单排序优化问题可归结为旅行商(Tranvelling salesman problem,TSP)问题。为求解模型,提出改进的K-Means聚类算法。计算每个订单与其他订单间的耦合因子,并对其进行排序;以单拣选台所有订单的耦合因子之和最大为目标,为每个拣选台分配订单并对订单进行排序。仿真结果显示,优化后系统拣选效率提高15.9%。     

串行分拣系统储区定位方法的研究

配送中心串行分拣作业系统中,产品相关性原则和工作量均衡原则是进行合理的分拣区储区定位、提高作业效率的2个重要原则。本文在充分研究这2个原则对串行分拣作业系统的影响的基础上,建立了工作区定位数学模型,应用数据挖掘中的关联规则方法挖掘产品品项间的相关性,并借鉴聚类思想提出启发式算法进行模型求解,最后将该方法应用于某配送中心的实际案例中,使用真实的运营数据仿真,验证了该方法的有效性。     

The optimum design of a warehouse system on order picking efficiency

From literature review and deep understanding on the practical industry, it is understood that the proper use of storage assignment policies can use minimum storage space to reach the purpose of minimum total traveling distance, and this has a direct impact on enhancing the order picking performance. At the same time, proper routing planning can minimize overall order picking cost, and finally reach the goal of picking performance enhancement in unit time. Therefore, this paper considers the effects on the order picking system performance for factors such as quantity and layout type of cross aisles in a warehouse system, storage assignment policy, picking route, average picking density inside an aisle, and order combination type, etc. A software, eM-plant, will be used as a simulation and analysis tool, a warehouse design database will be developed, which is based on the minimum overall traveling distance as the optimum performance index, the cross aisle quantity, warehouse layout, storage assignment, picking route planning, picking density and order combination type will be optimally integrated and planned in the warehouse system. Finally, we provide this database to the industry as a reference in the warehouse planning or warehouse design improvement in the future .     

双拣货区自动分拣系统品项分配优化

提前拣选、压缩合流的分拣策略使双拣货区自动分拣系统的拣选效率明显高于单拣货区自动分拣系统,基于此提出该策略下品项分配优化问题。介绍压缩合流的工作原理,确定双拣货区的品项分配对订单的压缩程度及提前拣选时间的影响。以负的各订单提前拣选时间之和最小为目标函数建立数学模型,该模型可归结为0-1规划问题并应用最大最小蚂蚁系统算法求解。实例仿真与分析证明了该算法的有效性。     

基于订单资料分析的配送中心规划及应用

现代化的配送中心是由多个储区、多种储存和分拣方式、多种设备配置和作业方式构成的错综复杂的物流系统,对其进行科学合理的规划设计是建设高效率配送中心的关键。在对配送中心系统规划进行长期研究和实践的基础上,提出需求分析、能力规划和详细规划的三段式配送中心系统规划方法论、基于订单资料分析的能力规划模型和基于储运模式的设备配置模型;详细阐述配送中心的储运单元设计、总体规模与能力规划、储区与储运模式规划、工艺流程设计以及基于EIQ-PCB的储区能力规划等原理和方法。最后介绍该规划方法在医药配送中心系统规划中的应用。     

ORDER-PICKING OPTIMIZATION FOR AUTOMATED PICKING SYSTEM WITH PARALLEL DISPENSERS

Based on the characteristics of parallel dispensers in automated picking system, an order-picking optimization problem is presented. Firstly, the working principle of parallel dispensers is introduced, which implies the time cost of picking each order is influenced by the order-picking sequence. So the order-picking optimization problem can be classified as a dynamic traveling salesman problem （TSP）. Then a mathematical model of the problem is established and an improved max-min ant system （MMAS） is adopted to solve the model. The improvement includes two aspects. One is that the initial assignment of ants depends on a probabilistic formula instead of a random deployment; the other is that the heuristic factor is expressed by the extra picking time of each order instead of the total. At last, an actual simulation is made on an automated picking system with parallel dispensers. The simulation results proved the optimization value and the validity of improvement on MMAS.     

考虑客户收货顺序的“货到人”分拣系统的订单排序和客户分批优化

可以并行分拣多个客户订单的"货到人"分拣系统中,每个客户包含多个订单,客户要求按订单排序依次收货。为提高该系统的分拣效率,以最小化料箱出入库数量为目标,从订单排序和客户分批两方面进行优化。分别建立两个0-1整数规划模型解决多客户同时拣选时的订单排序优化和客户分批优化问题;针对客户分批问题,又提出种子算法和遗传算法来解决。设计试验检验了不同客户数量、客户订单数量、总品项数量时订单排序模型和客户分批算法的优化效果。试验结果表明,0-1整数规划模型优化订单排序,可提高效率约15%,具有有效性;客户分批优化方面,0-1整数规划模型、遗传算法和种子算法都可以不同程度地提高系统效率,分别适合不同问题规模和时间要求的场景。     

Design and control of an AS/RS

Automated storage/retrieval systems (AS/RSs) are a combination of equipment and controls which automatically handle, store and retrieve materials (components, tools, raw material and subassemblies) with great speed and accuracy. Consequently, they are widely used in industrial companies to manage products with cost-effective utilization of time, space and equipment. This paper presents a multi-parametric dynamic model of a product-to-picker storage system with class based storage allocation of products. Thousands of what-if scenarios are simulated in order to measure the impact of alternative design and operating configurations on the expected system performance and to identify the most critical factors and combinations of factors affecting the response of the system. Class based storage proves to be a very effective way of both reducing the picking cycle time and maximizing the throughput of the system. The rapid effectiveness of visual interactive simulation (VIS) in supporting the design (redesign) and control of new (existing) warehouses emerges, responding to the need for flexibility which modern companies need in order to adapt to strongly changing operating conditions quickly.     

树莓采摘机闭式静液压行走系统研究

针对研究树莓采摘机闭式静液压行走系统设计方案,对国内树莓采摘机的发展现状以及液压行走系统在工程机械上的应用进行了研究,并结合树莓产业园的实际工况,进行方案的初步确定。分析了树莓采摘机的主要技术参数,进行液压元件的计算和选型,通过AMESim仿真分析液压泵在不同斜盘倾角下的流量—压力特性,提出了一种树莓采摘机闭式静液压行走系统方案。最后进行样机的试制与速度测试,验证方案设计的稳定性、可行性,以期为相关机械产品的设计提供技术参考。     

Taboo search algorithm for item assignment in synchronized zone automated order picking system

The idle time which is part of the order fulfillment time is decided by the number of items in the zone; therefore the item assignment method affects the picking efficiency. Whereas previous studies only focus on the balance of number of kinds of items between different zones but not the number of items and the idle time in each zone. In this paper, an idle factor is proposed to measure the idle time exactly. The idle factor is proven to obey the same vary trend with the idle time, so the object of this problem can be simplified from minimizing idle time to minimizing idle factor. Based on this, the model of item assignment problem in synchronized zone automated order picking system is built. The model is a form of relaxation of parallel machine scheduling problem which had been proven to be NP-complete. To solve the model, a taboo search algorithm is proposed. The main idea of the algorithm is minimizing the greatest idle factor of zones with the 2-exchange algorithm. Finally, the simulation which applies the data collected from a tobacco distribution center is conducted to evaluate the performance of the algorithm. The result verifies the model and shows the algorithm can do a steady work to reduce idle time and the idle time can be reduced by 45.63% on average. This research proposed an approach to measure the idle time in synchronized zone automated order picking system. The approach can improve the picking efficiency significantly and can be seen as theoretical basis when optimizing the synchronized automated order picking systems.     

Correlated storage assignment to minimize zone visits for BOM picking

The objective of this study is to design a correlated storage assignment system by storing items with demand dependences together to minimize zone visits when picking materials/parts in production line. The demand dependences can be obtained from the products’ bill of materials (BOMs) and production rates. Due to the large number of materials in a BOM, picking capacity constraint is explicitly considered. A mathematical model is formulated and heuristic algorithms are proposed, including two direct heuristics and two hybrid genetic algorithms with different crossover mechanisms. Numerical experimentation shows that the hybrid genetic algorithm with 2-point crossover outperforms others and can be practical in warehouse design.     

拣选式自动化仓库堆垛机作业路径简易优化算法

分析了自动化仓库堆垛机拣选作业的运行特点，给出了堆垛机拣选作业旅行商数学模型的常用优化算法。结合拣选作业的数学模型和固定货架的物理结构，构造了一种适合工程应用、编程简单的环状作业路径，并将该算法与最近邻居法和混合遗传算法进行了分析比较。仿真实验和工程实际应用表明，该算法能有效提高系统的工作效率。     

EIQ分析法在物流配送中心拣货系统设计中的应用

探讨了物流中心拣货系统的重要性,分析了拣货系统的EIQ法,并指出合理设计物流配送中心拣货系统,将有利于发挥物流配送中心的功能,提高物流配送中心的工作效率。     

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.     

果蔬采摘机器人的研究现状、问题及对策

为解决农业采摘中的实际问题,果蔬采摘机器人的研究与应用成为一种迫切需要.综述了国内外果蔬采摘机器人的研究进展与现状,介绍了几种典型的果蔬采摘机器人的研究成果.通过分析这些采摘机器人,指出了限制采摘机器人商品化的几点因素:采摘的效率、成功率及成本问题.并针对这些问题提出了解决对策,同时也指明了采摘机器人未来的研究方向.     

考虑气象因素的农业采摘机器人轨迹纠偏控制方法

为了减少气象因素对农业采摘机器人轨迹的影响,提出了考虑气象因素的农业采摘机器人轨迹纠偏控制方法,以解决机器人位姿精度较低和定位时间较长等问题。采用云储存技术对运动的目标果实进行检测与跟踪。利用改进的蚁群算法规划最优路径,通过 RBF 神经网络最佳逼近算法对动力学方程加以优化,加强其逼近能力,从而完成对采摘机器人轨迹纠偏的控制。实验结果表明,该方法可以有效地提高位姿精度、提高定位成功率、缩短定位时间并获得更为顺畅的采摘路径。