Heuristic algorithms for a storage location assignment problem in a chaotic warehouse

The extensive application of emerging technologies is revolutionizing warehouse management. These technologies facilitate working with complex and powerful warehouse management models in which products do not have assigned fixed locations (random storage). Random storage allows the utilization of the available space to be optimized. In this context, and motivated by a real problem, this article presents a model that looks for the optimal allocation of goods in order to maximize the storage space availability within the restrictions of the warehouse. For the proposed model a construction method, a local search algorithm and different metaheuristics have been developed. The introduced algorithms can also be used for other purposes such as to assess when and how it is convenient to perform relocation of stored items to improve the current level of storage space availability. Computational tests performed on a set of randomly generated and real warehouse instances show the effectiveness of the proposed methods.     

Order picking system design: the storage assignment and travel distance estimation (SA&TDE) joint method

Of all the warehouse activities, order picking is one of the most time-consuming and expensive. In order to improve the task, several researches have pointed out the need to consider jointly the layout of the warehouse, the storage assignment strategy and the routing policy to reduce travelled distances and picking time. This paper presents the storage assignment and travel distance estimation (SA&TDE) joint method, a new approach useful to design and evaluate a manual picker-to-parts picking system, focusing on goods allocation and distances estimation. Starting from a set of picking orders received in a certain time range, this approach allows to evaluate the combinations of product codes assigned to storage locations, aisles, sections or warehouse areas and to assess the most relevant ones, for the best location and warehouse layout, with the aim of ensuring optimal picking routes, through the application of the multinomial probability distribution. A case study is developed as well, in order to clarify the concept that underlies the SA&TDE joint method, and to show the validity and the flexibility of the approach, through the calculation of the saving at different levels of detail.     

Intelligent agent modeling of an industrial warehousing problem

In this paper, we consider an actual industrial warehouse order picking problem where goods are stored at multiple locations and the pick location of goods can be selected dynamically in near real time. We solve the problem using an intelligent agent-based model. The modeling framework is between the two extremes of hierarchical and heterarchical frameworks. It recognizes that horizontal as well as vertical decisions are made between various levels of controllers and that these have to be captured explicitly in the model. Entities (goods or parts) and resources (storage areas and order pickers) are modeled as intelligent agents that function in a co-operative manner so as to accomplish individual as well as system-wide goals. Scheduling and other decisions are taken by these agents in a dynamic real-time fashion based on conditions that exist at the time these decisions are made. To overcome the structural rigidity and lack of flexibility, a negotiation mechanism for real time task allocation is used     

多色集合在仓配一体化仓库货位分配建模中的应用

目的为了提高仓配一体化仓库的货物存储以及货物周转效率,对仓库货位分配进行研究。方法以西北地区某快消品仓配一体化配送中心仓库为背景,应用多色集合理论建立仓配一体化仓库中货位信息模型,通过实际案例对建立的模型进行仿真实验,得出仓库中货位的最优分区。结果对仓库在货物就近原则放置和货物分区管理下车辆的等待时间进行仿真,限定在100 d的时间里,得出仓库在运用多色集合理论分区的情况下装卸车辆等待时间相比之前未分区时间下降了20.84%。结论运用多色集合理论有效提高了城市快消品仓配一体化中货位优化的效率。     

Ergonomic workplace design in the fast pick area

The aging society in many developed countries has made an ergonomic workplace design to an important topic among researchers and practitioners alike. We investigate the workplace design for order pickers that manually collect items from the shelves of a warehouse. Specifically, we treat the storage assignment, i.e., the placement of products in shelves of different height, and zoning, i.e., the partitioning of the storage space into areas assigned to separate pickers, in the fast pick area of a warehouse. A fast pick area unifies the most fast-moving items in a compact area, so that workers are relieved from unproductive travel, but face extraordinary ergonomic risks due to the frequent repetition of picking operations. Concerning the health of (aged) workers, it is crucial to reduce such risks. Thus, we define a combined ergonomic storage assignment and zoning problem with the objective of minimizing the maximum ergonomic burden among all workers. This problem is formalized, and two construction heuristics and a tabu search procedure are proposed. Our results show that neglecting ergonomic aspects and only focusing on picking performance leads to much higher ergonomic risks of the workforce.

     

Differentiated service policy in smart warehouse automation

Smart warehouse automation has emerged as an effective, competitive solution for suppliers and distributors. With the increasing demand for physical storage and distribution services, suppliers and service providers are challenged to respond not only effectively, but with minimal latency. Differentiated service levels for different classes of customer orders have not yet, however, been developed for physical storage and retrieval. In this paper, in the context of smart warehouse automation services, a novel policy, called Differentiated Probabilistic Queuing (DPQ) is developed for servicing customers’ orders by Automated Guided Vehicles (AGV). Applying the DPQ policy, the average overall latency of each customer order, the mean overall processing time of this customer’s orders in the smart warehouse automation system, is characterised under Poisson customer order arrival patterns. The weighted average latency of all customer orders is optimised over the choice of (1) storage assignment and (2) DPQ policy. Due to the existence of two types of variables, Alternating Minimisation method is applied to solve this joint optimisation problem. Compared with a combination of the classical turn-over rate storage assignment method and FCFS policy, the new approach yields 19.64% lower (better) objective function value with statistical significance. Numerical analysis results also indicate, as expected, that when the smart warehouse system resources become more limited, and the price difference among different classes of customer orders increases, the improvement becomes even more significant.     

基于FlexSim 的军队自动化立体仓库货位优化研究

为提高军队自动化立体仓库出货速度和运行稳定性,提出了在堆垛机闲时对货位进行以分类存储L 形分区为导向的再分配优化设计。根据用户需求,程序自动生成分类存储的L 形分类存储货位分区信息,并调用堆垛机对在存货品逐一判断、搬运,让所有货品按照L 形区域排列,完成货位优化。利用FlexSim 软件对具体实例进行了仿真,结果表明,优化后的货位能较大程度地提高仓库的输出效率。     

Analytical models for pick distances in fishbone warehouse based on exact distance contour

The pick distance models for a unit load warehouse employing fishbone layout conventionally use semicircular approximation for distance contour which can result in significant error. This paper develops discrete and continuous pick distance models for fishbone layout under random, full turnover, and class-based storage policies based on exact polygonal distance contour. Class-based storage policy with three classes was found to give pick distance comparable to full turnover policy over a range of demand skews and warehouse shapes studied. The discrete and continuous models are compared considering finite storage space, aisle width and discontinues in the ABC curve for a real life data. The sensitivity of warehouse performance over a range of warehouse parameters is studied. We also outline a methodology for class-based storage design where class partitions can be derived for a warehouse of any dimension from the results of a unit area warehouse.     

Auto Store仓储系统的运作与效率优化研究

目的 为缓解零售电商商品仓库占地面积广,拣选效率受限等问题。方法 文中就存储策略、指派策略以及路径策略方面对Auto Store仓储系统进行详尽的介绍,在此基础上流程化的分析Auto Store系统完成单次订单拣货作业的业务流程,并运用Anylogic软件对所提出的模型进行仿真和验证。结果 假定订单到达服从Erlang分布,在拣选车和工作站数量和拣选货物数量相同的情况下,对比了Auto Store仓储系统混存布局和传统布局的拣选效率,验证了混存布局的可行性。结论 同时对比基于2种任务指派策略,得出了以基于拣选时间最小化的指派策略下系统运作效率更优这一结论,对理论分析与仿真研究之间的结果进行分析比较,验证了模型的有效性。     

可变路径人工拣货系统动态货位调整研究

考虑在线零售企业的时变需求,基于逐步求精、渐进式优化的思路,通过实时、动态调整商品在仓库中的存储位置来响应需求的快速变化,并允许拣货员改变其行走路线,在订单拣货的同时进行货位调整。构建了可变路径下动态货位调整框架模型;提出前进和返回交替进行的回转路径策略,并对路径调整策略及商品选择策略两个关键进行研究;通过实验验证模型的有效性。结果表明,在订单规模中等,需求偏度较大时,动态货位调整可节约25%左右的拣货距离,货位优化效果明显,可为在线零售企业科学实施动态货位调整提供理论指导。     

Management optimisation based on dynamic SKU for RFID-enabled warehouse management in the steel supply chain

Radio-frequency identification (RFID) technology is one of the encouraging technologies to improve the productivity in warehouse management. However, the problem of how to explore the potential benefits of a RFID system and reduce the expenditure of RFID application are troubling many managers who are planning to, or have engaged in, the implementation. This paper enriches existing theory by introducing the useful and comprehensive warehouse management optimisation methods based on dynamic SKU (storage keeping unit) management in the design and development of a RFID-enabled warehouse. Based on the dynamic SKU management method proposed, cost optimisation methods are employed in the development of RFID-enabled warehouse. Furthermore, a storage area management optimisation for multi-size coils and a crane scheduling optimisation method is established for the purpose of enhancing the productivity of the warehouse. The optimisation methods are applied and verified in a coil warehouse and the result shows that the hardware investment is cut down by reducing the number of RFID cards used without any decrease in location accuracy and the warehouse productivity is improved significantly.     

基于英式拍卖的RMFS货位指派研究

目的 构建英式拍卖模型，以待指派商品品项(SKU)群的最低周转率为媒介，通过逐步提升最低周转率来实现待指派SKU与待指派区域货位数量的匹配。方法 针对移动机器人拣货系统(RMFS)中的货位指派，提出基于英式拍卖机制的货位指派方法，提升仓库拣货效率。结果 与随机指派相比，在不同仓库规模、订单规模、订单偏度的RMFS中采用英式拍卖货位指派机制，机器人行走路程下降比率在大型仓库中达30.17%，中型仓库的下降比率为27.31%，小型仓库的下降比率为24.13%。结论 采用英式拍卖机制在RFMS中进行货位指派可大幅度提高工作效率。     

现代仓储中心存储布局的优化研究

仓储中心的货架摆放布局是影响拣选作业效率的重要因素之一,为研究货架摆放布局对有效存储面积的影响,以鱼骨布局为研究对象,构建其有效存储面积利用率模型,并对其进行仿真验证。结果表明,在鱼骨布局设计的仓库中,主拣选通道角度一定时,拣选通道宽度与货架宽度比例越大,有效存储面积利用率越小;拣选通道宽度与货架宽度比例一定时,主拣选通道角度越趋近于0度或者90度时,有效存储面积利用率越大。由此,鱼骨布局等改进型仓储布局为决策拣选路径提供了新的思路,也从理论上证明了改进型仓储布局实践应用的可行性。     

危险品智能仓储及运输管理系统的电磁安全

目的开发满足炸药、火工品等危险品使用的智能仓储及运输管理系统,以提高危险品物流的信息化和智能化管理水平。方法采用RFID技术设计危险品信息识别系统,分析炸药和火工品等危险品在系统常用频率和电场强度下的响应特性,并研究其电磁安全性。结果危险品信息识别系统在13.6 MHz和915 MHz等2种频率下可以用于危险品仓储和运输管理。结论研制了危险品智能仓储及运输管理系统,明确了其安全使用要求。应根据具体场景综合分析危险品的特征频率和安全射频功率,建立适合的安全性评价方法和标准,以保证安全。     

Expected travel time and optimal boundary formulas for a two-class-based automated storage/retrieval system

Our paper studies a two-class-based rectangular-in-time automated storage/ retrieval system (AS/RS). We present explicit formulas for the optima! boundary of the two storage areas as well as for the expected single command cycle time for an optimally designed rack. In the basic model each crane handles a single aisle. These formulas provide the designer with a full picture of the quantitative effects of the various factors (i.e., access frequencies of the two storage areas, and dimensions of the rack) on the optimal boundary of the two storage areas and the achievable cycle lime in the warehouse. We also develop expected travel time formulas for the dual command AS/RS with two-class-based storage policies and obtain the optimal boundary with a one-dimensional search procedure. Similar developments (i.e., expected travel time formulas and optimal boundary search procedures) are discussed for AS/RS with a single command policy but with each crane handling multiple aisles.     

AN APPLICATION OF CLUSTER ANALYSIS TO THE PROBLEM OF LOCATING ITEMS WITHIN A WAREHOUSE

The order picking function in a warehouse involves selection of items from storage areas in order to satisfy customer demand. It has been identified as the most costly warehouse operations activity. Cluster analysis identifies groups of items that are frequently ordered together. Items within a cluster may be located near one another, and efficient picking tours may, thus, be formed. We formulate the clustering problem as a p-median 0-1 integer program which may efficiently be solved to optimality.     

Simulation-based regression analysis for the rack configuration of an autonomous vehicle storage and retrieval system

In this paper, a simulation-based regression analysis for the rack configuration of an autonomous vehicle storage and retrieval system (AVS/RS) is presented. The aim of this study is to develop mathematical functions for the rack configuration of an AVS/RS that reflects the relationship between the outputs (responses) and the input variables (factors) of the system under various scenarios. In the regression model, we consider five outputs: the average cycle time of storage and retrieval transactions, the average waiting time for vehicle transactions, the average waiting time of vehicles (transactions) for the lift, the average utilisation of vehicles and the average utilisation of the lifts. The input variables are the number of tiers, aisles and bays that determine the size of the warehouse. Thirty regression models are developed for six warehouse scenarios. The simulation model of the system is developed using ARENA 12.0 commercial software and the statistical analyses are completed using MINITAB statistical software. Two different approaches are used to fit the regression functions–stepwise regression and the best subsets. After obtaining the regression functions, we optimise them using the LINGO software. We apply the approach to a company that uses AVS/RS in France.     

Normative Models for Some Warehouse Sizing Problems

The problem examined is the determination of the optimum size for a warehouse used to store products over a finite planning horizon. Both fixed and changeable warehouse size problems are treated under conditions of deterministic and probabilistic storage demand. The latter is formulated as a linear programming problem and transformed via duality theory into an equivalent network flow problem for efficient solution. Costs considered are those due to warehouse construction, storage of products within the facility, and storage demand not satisfied by storage in the warehouse.     

Optimal partitioning of vertical zones in vehicle-based warehouse systems

New innovations in warehouse automation systems such as autonomous vehicle-based storage and retrieval (AVS/R) system offer greater flexibility and responsiveness in processing unit-load storage and retrieval transactions in high-density storage areas. To optimise system performance, new technologies should be implemented with optimal setting of design parameters. This research is a first attempt to model a ‘zone-captive’ AVS/R system and understand the effect of number and boundary of vertical zones on system performance measures. Further, we also analyse the effect of aisle orientation within a tier on cycle times. A detailed simulation model of a multi-tier zone-captive system is built to capture the dynamics of the system i.e. interaction among the vehicles, lift and incoming transaction requests, and estimate the performance measures of interest. The numerical experiments show that the transaction cycle times can be reduced by 1–12% with optimal partitioning of vertical zones and further reduced by 0.2–15.0% by a better aisle orientation.     

面向冷链智能立体仓库的数字孪生系统构建

目的 当前冷链物流行业立体仓库存在货品损耗率高、失温严重、信息化水平低等问题,确保冷链智能立体仓库的食品质量安全,并实现降本增效。方法 面向冷链智能立体仓库的运行场景,设计全映射与多维仿真的数字孪生五维模型,通过对多源异构数据的融合,实现立体仓库全要素的状态实时可视化与监测预警,并提出一种支持系统联动决策的模型优化策略,对立体库负载与温控区热力分布进行智能调节,最大限度提高运行效率和降低运营成本。结果 构建了一套冷链智能立体仓库数字孪生系统,通过对优化前后仓库运行数据进行对比,同等仓储环境条件下生鲜蔬菜的食品保鲜度损耗率同比下降了25%~30%,实现了冷链智能立体仓库实时数据与动态虚拟模型的精准映射与联动运转。结论 以广东某供应链管理有限公司佛山智能冷链仓储物流中心的冷链立体仓库为实践对象,形成了冷链智能立体仓库一体化管控新模式。为冷链智能立体仓库运营管理、调度联动决策与协同作业提供了数字孪生技术的应用参考,为建立更完善的保鲜产品包装与冷链食品质量安全提供了新路径。