Impact of required storage space on storage policy performance in a unit-load warehouse

The performance of a storage policy in a warehouse is usually evaluated on the basis of the average one-way travel distance/time needed to store/retrieve a load. Dividing the storage space into zones based on item turnover frequency can reduce the travel distance. However, for a given number of stored items, a larger number of storage zones also requires more storage space, because of reduced space sharing between the items, which increases travel time. This study considers the required space consumption by storage zoning in comparing the performance of random, full turnover-based and class-based storage policies for a unit-load warehouse operated by a forklift in single-command mode. A generalised travel distance model that considers the required space consumption is developed to compare the performance of these policies. Results show that the one-way travel distance of a random policy decreases with the increase in skewness of the demand curve. By considering the required space consumption, a class-based storage policy performs generally better than a full turnover-based policy. In addition, the optimal warehouse shape factor (ratio of warehouse width to depth) appears to decrease with the skewness of the demand curve. Warehouse managers are advised to adopt a wide-shallow warehouse layout when the item demands are approximately equal, whereas a narrow-deep layout is preferred when the demand curves are steep.     

Analytical models for a new turnover-based hybrid storage policy in unit-load warehouses

This paper considers a low-level unit-load warehouse employing single-deep storage lanes and a single-command manual storage and retrieval policy. Analytical travel distance models are developed for class-based and full turnover storage policies under across-aisle, within-aisle and a newly proposed hybrid product placement schemes. Our computational studies show that the analytical models developed in this paper are very accurate as compared to simulation results and a comparative study with a real-world warehouse case. Hybrid storage policies proposed in this paper outperform all other traditional storage policies. The paper also presents insights and simple design rules to warehouse practitioners.     

A heuristic approach to warehouse layout with class-based storage

This paper presents a procedure for warehouse layout. It employs the principles of class-based storage to increase floor space utilization and decrease material handling. Three phases of the procedure are outlined: (1) determination of aisle layout and storage zone dimensions, (2) assignment of material to a storage medium, and (3) allocation of floor space. An industrial case study illustrates the procedure for a warehouse required to store 739 different products totaling more than 10000 pallets of material. An improved layout was developed and compared with the existing alternative. The proposed layout offered savings of more than 20 000 square feet of floor space and an approximately 45% reduction in material handling distance.     

A framework for the dual command cycle travel time model in automated warehousing systems

This paper proposes a framework for the dual command cycle continuous travel time model under class-based assignment. The ABC distribution is incorporated into the model as the inventory turnover function. The evaluation of the continuous approximation and the improvements of class-based assignment over random storage with various inventory turnover functions are also presented.     

基于鱼骨型仓库布局的多车拣选路径问题优化

为了推动鱼骨型仓库在实际场景下的应用,针对鱼骨型仓库布局下的拣货路径优化问题,构建待拣货点距离计算模型和以有载重、容积限制的多车拣货距离最短为总目标的拣选路径优化模型。考虑遗传算法(GA)全局搜索能力强、粒子群算法(GAPSO)收敛速度快以及蚁群算法(ACO)较强的局部寻优能力,提出一种解决拣选路径优化模型的混合算法(GA-PSO-ACO)。通过不同订单规模的仿真实验,得出该混合算法在适应度值、迭代次数、收敛速度等方面均优于GA算法和GAPSO算法,且在订单规模较大时,平均适应度值约降低8%,有效缩短了总拣选距离,验证了混合算法在解决鱼骨型仓库布局下的拣货路径问题的先进性和有效性,为解决此类仓库内部的拣货路径问题提供新的解决方法和思路。     

Travel distance estimation and storage zone optimization in a 2-block class-based storage strategy warehouse

Order picking has been considered as the most critical operation in warehousing. Recent trends in logistics demand faster but more reliable order picking systems. The efficiency of an order picking process greatly depends on the storage policy used, i.e. where products are located within the warehouse. In this paper, we deal with the most popular storage policy that is class-based (or ABC) storage strategy. Particularly, we investigate the problem of determining the optimal storage boundaries (zones) of classes in each aisle for manually operated warehouses.

We first propose a probabilistic model that enables us to estimate the average travel distance of a picking tour. We found that the differences between results obtained from simulation and the model were slight. Using the average travel distance as the objective function, we present a mathematical formulation for the storage zone optimization problem. However, the exact approach can handle only small size warehouse instances. To circumvent this obstacle, we propose a heuristic for the problem. Numerical examples we conducted show that the heuristic performs very well in all the cases.     

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.     

An evaluation of routing policies for order-picking operations in low-level picker-to-part system

This paper evaluates the performance of three routing policies in the order-picking process, i.e. return, traversal, and midpoint policy. It is assumed that items are assigned to storage locations on the basis of the cube-per-order index (COI) rule in a low-level picker-to-part warehousing system. First, for the three policies, analytical models are developed for the total expected travel distance of the order picker considering the number of the stocking aisles is even or odd. Then the developed models are compared with simulation results to show the validity. Finally, the performance of the three policies is examined by varying the parameter value of the COI-based ABC curve, number of picks in the pick list, and ratio of the length to the width of the warehouse.     

Location and layout planning

This paper gives a review on quantitative methods for microeconomic location planning which can be subdivided into facility location and layout planning. Depending on different objectives and restrictions, there is a large variety of problems, especially in the field of facility location planning. Basic models arising in discrete and continuous facility location planning (e.g., warehouse location, center, location routing, competitive location problems), as well as corresponding solution methods, are presented. Generalized models and recent developments in these fields are outlined. Within layout planning, the quadratic assignment problem and graph-theoretic concepts are considered.     

Concurrent manual-order-picking warehouse design: a simulation-based design of experiments approach

The design of manual-order-picking warehouses is a combination of interdependent decisions with enormous possible varieties in design components. The strong interrelationship between these components, in addition to the dynamic and interconnected stochastic nature of the problem; necessitate the utilisation of a simultaneous simulation-based approach. This study proposes a concurrent simulation-based design of experiments approach for the design of manual-order-picking warehouses. The proposed approach can investigate all possible warehousing design combinations with their stochastic nature and interactions; hence, widening the search for performance improvement. The examined design components include warehouse throughput, size, layout, operational policies and manpower/carts. Furthermore, the presented approach captures the probabilistic nature of all the key warehouse functions of receiving, unloading, put away, storage, preparation and picking and shipping; and evaluates the performance of the studied designs using the cycle time for a stock keeping unit in the warehouse. Statistical analysis of the simulation results showed several interesting findings; horizontal layout was preferable over all other types of layouts and small size warehouses perform better than other large sizes. The study has also recommended using high throughput for traditional layout-small size warehouses.     

Robotics in order picking: evaluating warehouse layouts for pick,place, and transport vehicle routing systems

Motivated by recent technological advances in mobile robotics, this paper explores a novel approach for warehouse order picking. In particular, this work considers two types of commercially available mobile robots – one that can grasp items from a shelf (a picker) and another (a transporter) that can quickly deliver all items from the pick list to the packing station. A new vehicle routing problem is defined which seeks to minimise the time to deliver all items from a pick list to the packing station, a problem termed the pick, place, and transport vehicle routing problem. A mixed integer linear programming formulation is developed to answer three related research questions. First, what combination of picker and transport robots is required to obtain performance exceeding traditional human-based picking operations? Second, how should the composition of the robot fleet be altered to affect the greatest performance improvements? Finally, what are the impacts of warehouse layout designs when coordinated mobile robots are deployed? An extensive numerical analysis reveals that, (1) increasing the number of cross aisles decreases system performance; (2) centrally located packing stations improve system performance; and (3) the average distance from each pick location to the packing station and the average distance between pick locations are effective metrics for identifying specific fleet modifications that are likely to yield system improvements.     

Routing methods for warehouses with multiple cross aisles

This paper considers routing and layout issues for parallel aisle warehouses. In such warehouses order pickers walk or drive along the aisles to pick products from storage. They can change aisles at a number of cross aisles. These cross aisles are usually located at the front and the back of the warehouse, but there can also be one or more cross aisles at positions in between. We describe a number of heuristics to determine order picking routes in a warehouse with two or more cross aisles. To analyse the performance of the heuristics, a branch-and-bound algorithm that generates shortest order picking routes is used. Performance comparisons between heuristics and the branch-and-bound algorithm are given for various warehouse layouts and order sizes. For the majority of the instances with more than two cross aisles, a newly developed heuristic appears to perform better than the existing heuristics. Furthermore, some consequences for layout are discussed. From the results it appears that the addition of cross aisles to the warehouse layout can decrease the handling time of the orders by lowering average travel times. However, adding a large number of cross aisles may increase average travel times because the space occupied by the cross aisles has to be traversed as well.     

The effect of warehouse cross aisles on order picking efficiency

This paper investigates the effects of adding cross aisles to the layout of an order consolidation warehouse, with respect to order picking efficiency. Intuitively, cross aisles provide greater flexibility in the routing of order pickers, thus providing shorter order picking travel distances. However, this effect may be negated when the number of cross aisles becomes excessive, as the cross aisles themselves must be traversed in order to reach the required items. A shortest path pick sequencing model is developed which allows for any number of cross aisles in the warehouse. The optimal routing is computed for a large number of randomly generated picking requests, over a variety of warehouse layout and order picking parameters. The results are used to characterize the optimal number of warehouse cross aisles, as well as the conditions under which cross aisles generate the greatest benefit.     

Improvement of AS/RS performance using design and application of common zone

Minimization of overall queue length in AS/RS is studied in this research. In general, class-based storage policy is recommended for overall AS/RS operation, but it has a rack shortage problem under demand variation. To resolve this problem, an area along the board of two classes in AS/RS racks is allocated and is named the common zone. This zone is designed to handle the rack shortage problem associated with the items in a particular class under class-based storage policy. Thirty percent common zone size is determined as the most favorable allocation among various sizes through simulation experiments. This particular size common zone policy is compared with other well-known policies such as class-based, relocation, and random storage policy. These four operation policies under three different levels of workloads with demand variations are simulated. Crane moving time, rack shortages, delay times as well as throughputs are checked for the policy evaluation.     

A model for warehouse layout

This paper describes an approach to determine a layout for the order picking area in warehouses, so that the average travel distance for the order pickers is minimized. We give analytical formulas that can be used to calculate the average length of an order picking route under two different routing policies. The optimal layout can be determined by using these formulas as the objective function in a nonlinear programming model. The optimal number of aisles in an order picking area appears to depend strongly on the required storage space and the pick list size.     

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。     

基于COI与作业负荷平衡的多巷道仓库储位分配策略

储位分配策略直接影响仓储货品的拣选效率与仓库绩效。传统基于物料周转率（COI）的储位分配方法将出入库频率高的货物存储于距离出入口近的储位上,在多巷道分布的仓库当中,这可能导致部分巷道作业拥堵和事故发生率高等。为提升仓储货品拣选效率和减少巷道作业不平衡带来的负面影响,本研究将基于COI储位分配方法与巷道作业平衡改进策略相结合,通过定性解析与模型分析,提出绝对分巷道存储模型和相对平均与最大值控制模型两种储位分配改进方法。通过实例数据分析,两种新方案对行走距离增加值可控制于千分之一以内,而新最优可行解对完善仓储策略和进一步提升仓储企业效率有着重要作用。     

Enhancing performance in order picking processes by dynamic storage systems

Increasing productivity and reducing labour cost in order picking processes are two major concerns for most warehouse managers. Particularly picker-to-parts order picking methods lead to low productivity as order pickers spend much of their time travelling along the aisles. To enhance order picking process performance, an increasing number of warehouses adopt the concept of dynamic storage where only those products needed for the current order batch are dynamically stored in the pick area, thereby reducing travel time. Other products are stored in a reserve area. We analyse the stability condition for a dynamic storage system with online order arrivals and develop a mathematical model to derive the maximum throughput a DSS can achieve and the minimum number of worker hours needed to obtain this throughput, for order picking systems with a single pick station. We discuss two applications of dynamic storage in order picking systems with multiple pick stations in series. In combination with simulation modelling, we are able to demonstrate that dynamic storage can increase throughput and reduce labour cost significantly.     

Evaluating order throughput time with variable time window batching

Given increased pressure to provide short delivery times, minimising customer order throughput time is a very important objective in warehousing operations. There are many factors that may affect the performance of an order picking system, such as layout of the warehouse, the storage strategy, the routing policy, the zoning method and the batching policy. In this study, we propose a simple travel time model and analyse the effect of order batching on the expected customer order throughput time with variable time window batching. In addition, we discussed the impact of some parameters on the batch size and the expected customer order throughput time. In the practice of Wuhan Dong Hon Logistics co. Ltd, the storage rack in the warehouse has two levels: the low storage level and the high storage level. These two levels are visited by pickers and forklifts, respectively. The classification improves the performance of order picking. In this study, we build the model based on this practice.     

Optimal layout in low-level picker-to-part systems

The paper presents an analytical approach to layout design of the picking area in low-level, picker-to-part systems using COI (cube per order index)-based and random storage policies. The layout of the picking area is one of the major issues in increasing picking system productivity, i.e. in reducing the time required to complete a given set of orders, and must take account of the inter-relationship between the main operating policies, i.e. storage, routing and batching. The main system parameters affecting the layout design are the total length of the picking aisles, the number of pick stops per tour and the shape of the COI-based ABC curve. A formula that relates the optimal number of aisles to the above parameters will be presented, together with the increase in the expected tour distance stemming from the adoption of a non-optimal number of aisles. The study thus provides a comprehensive framework for layout design.