René de Koster

Design and control of warehouse order picking: A literature review

Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for the warehouse, and consequently for the whole supply chain. In order to operate efficiently, the order-picking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.

Transshipment of containers at a container terminal: An overview

At container terminals, containers are transshipped from one mode of transportation to another. Within a terminal different types of material handling equipment are used to transship containers from ships to barges, trucks and trains and vice versa. Over the past decades, ships have strongly increased in size, up to 8000 TEU (Twenty feet equivalent unit container). In order to use these big ships efficiently, the docking time at the port must be as small as possible. This means that large amounts of containers have to be loaded, unloaded and transshipped in a short time span, with a minimum use of expensive equipment. This paper gives a classification of the decision problems that arise at container terminals. For various decision problems, an overview of relevant literature is presented. Quantitative models from this literature, which try to solve the problems are discussed. Finally, some general conclusions and subjects for further research are given. 2002 Elsevier Science B.V. All rights reserved.

Routing order pickers in a warehouse with a middle aisle

This paper considers a parallel aisle warehouse, where order pickers can change aisles at the ends of every aisle and also at a cross aisle halfway along the aisles. An algorithm is presented that can find shortest order picking tours in this type of warehouses. The algorithm is applicable in warehouse situations with up to three aisle changing possibilities. Average tour length is compared for warehouses with and without a middle aisle. It appears that in many cases the average order picking time can be decreased significantly by adding a middle aisle to the layout.

Linking warehouse complexity to warehouse planning and control structure: An exploratory study of the use of warehouse management information systems

Warehousing is becoming more and more a critical activity in the supply chain to outperform competitors on customer service, lead times, and costs. However, if warehousing is to be a source of competitive advantage, then the implementation of a warehouse management information system (WMS) is a necessary condition to achieve efficiently the high performance of warehousing operations required in today’s marketplace. A major practical question is then whether a given warehouse should implement a standard or a tailor‐made WMS. A standard WMS offers many advantages; it is a proven solution, it is less costly, the implementation lead time is shorter, and the after‐sales service is better. On the other hand, a standard WMS remains largely making compromises between the way a warehouse wants to work and the way the system allows the warehouse to work. In certain environments, such compromises might seriously degrade warehouse performance, in which case it then seems better to implement a tailor‐made WMS. To answer the above question, we conducted an exploratory field study of warehouses with recently implemented WMSs to first understand the empirical reality and then build up a theory linking the constructs warehouse complexity and warehouse planning and control structure. Warehouse complexity refers to the number and variety of items to be handled, the degree of their interaction, and the number, nature, i.e. technologies used, and variety of processes, determined among others by the warehouse’s position in the logistic chain and the nature of its market. Warehouse planning and control structure refers to the management functions that plan, direct, coordinate and control the flow of goods through the warehouse, from the time of receiving to the time of shipping. It is strongly related to the WMS in use. We found that the number of orderlines to be processed per day and the number of stock‐keeping units are the two main observable aspects of warehouse complexity; that the more complex the warehouse is, the more tailor‐made the planning and control structure should be; that for simple warehouses a standardized planning and control structure suffices; and that the design of a new‐to‐build warehouse should be carried out in close concert with the design of the warehouse planning and control structure.

Travel time estimation and order batching in a 2-block warehouse

textabstractThe order batching problem (OBP) is the problem of determining the number of orders to be picked together in one picking tour. Although various objectives may arise in practice, minimizing the average throughput time of a random order is a common concern. In this paper, we consider the OBP for a 2-block rectangular warehouse with the assumptions that orders arrive according to a Poisson process and the method used for routing the order-pickers is the well-known S-shape heuristic. We first elaborate on the first and second moment of the order-pickers travel time. Then we use these moments to estimate the average throughput time of a random order. This enables us to estimate the optimal picking batch size. Results from simulation show that the method provides a high accuracy level. Furthermore, the method is rather simple and can be easily applied in practice.

Minimum Vehicle Fleet Size Under Time-Window Constraints at a Container Terminal

Products can be transported in containers from one port to another. At a container terminal these containers are transshipped from one mode of transportation to another. Cranes remove containers from a ship and put them at a certain time (i.e., release time) into a buffer area with limited capacity. A vehicle lifts a container from the buffer area before the buffer area is full (i.e., in due time) and transports the container from the buffer area to the storage area. At the storage area the container is placed in another buffer area. The advantage of using these buffer areas is the resultant decoupling of the unloading and transportation processes. We study the case in which each container has a time window [release time, due time] in which the transportation should start.The objective is to minimize the vehicle fleet size such that the transportation of each container starts within its time window. No literature has been found studying this relevant problem. We have developed an integer linear programming model to solve the problem of determining vehicle requirements under time-window constraints. We use simulation to validate the estimates of the vehicle fleet size by the analytical model. We test the ability of the model under various conditions. From these numerical experiments we conclude that the results of the analytical model are close to the results of the simulation model. Furthermore, we conclude that the analytical model performs well in the context of a container terminal.

Distribution structures for food home shopping

In this paper, the relation between the constructs operational complexity, Web‐based orientation of the company and the company’s distribution structure used for the fulfilment of Internet customer orders is investigated in the food home shopping branch. A model is proposed with relations between these constructs, which is researched through a survey among food e‐tailers. A positive association between operational complexity and the distribution structure used could be established, meaning that more complex operations (with a full‐line assortment and a large number of orders) tend to have special (Internet orders only) distribution centres for the fulfilment of Internet customer orders. Companies with a store infrastructure tend to keep using this existing infrastructure (unless the number of orders becomes large) and new Internet‐only companies tend to use special Internet‐orders only warehouses, unless the number of orders is small, in which case co‐operation with existing stores is preferred.

The impact of order batching and picking area zoning on order picking system performance

This paper proposes an approximation model based on queuing network theory to analyze the impact of order batching and picking area zoning on the mean order throughput time in a pick-and-pass order picking system. The model includes the sorting process needed to sort the batch again by order. Service times at pick zones are assumed to follow general distributions. The first and second moments of service times at zones and the visiting probability of a batch of orders to a pick zone are derived. Based on this information, the mean throughput time of an arbitrary order in the order picking system is obtained. Results from a real application and simulation show that this approximation model provides acceptable accuracy for practical purposes. Furthermore, the proposed method is simple and fast and can be easily applied in the design and selection process of order picking systems.

Designing an optimal turnover-based storage rack for a 3D compact automated storage and retrieval system

Compact, multi-deep (3D) automated storage and retrieval systems (AS/RS) are becoming increasingly popular for storing products. We study such a system where a storage and retrieval (S/R) machine takes care of movements in the horizontal and vertical directions of the rack, and an orthogonal conveying mechanism takes care of the depth movement. An important question is how to layout such systems under different storage policies to minimize the expected cycle time. We derive the expected single-command cycle time under the full-turnover-based storage policy and propose a model to determine the optimal rack dimensions by minimizing this cycle time. We simplify the model, and analytically determine optimal rack dimensions for any given rack capacity and ABC curve skewness. A significant cycle time reduction can be obtained compared with the random storage policy. We illustrate the findings of the study by applying them in a practical example.

Performance approximation of pick-to-belt orderpicking systems

textabstractIn this paper, an approximation method is discussed for the analysis of pick-to-belt orderpicking systems. The aim of the approximation method is to provide an instrument for obtaining rapid insight in the performance of designs of pick-to-belt orderpicking systems. It can be used to evaluate the effects of changing the layout of the system, the number of picking stations, the number of pickers, the conveyor speed, the number of bins to be processed per day, the number of orderlines per bin, etc. Especially in the design phase, modeling and analysis speed is more important than accuracy. The method presented in this paper is based on Jackson network modeling and analysis. The method is fast and sufficiently accurate. The method is used by Ingenieursbureau Groenewout B.V., for early-stage evaluation of design alternatives of pick-to-belt orderpicking systems and general transportation systems.