Invited Review
Design and control of warehouse order picking: A literature review

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Abstract

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.

Introduction

As more companies look to cut costs and improve productivity within their warehouses and distribution centres, picking has come under increased scrutiny. Order picking – the process of retrieving products from storage (or buffer areas) in response to a specific customer request – is the most labour-intensive operation in warehouses with manual systems, and a very capital-intensive operation in warehouses with automated systems (Goetschalckx and Ashayeri, 1989, Drury, 1988, Tompkins et al., 2003). For these reasons, warehousing professionals consider order picking as the highest-priority area for productivity improvements.

Several recent trends both in manufacturing and distribution have made the order-picking design and management become more important and complex. In manufacturing, there is a move to smaller lot-sizes, point-of-use delivery, order and product customisation, and cycle time reductions. In distribution logistics, in order to serve customers, companies tend to accept late orders while providing rapid and timely delivery within tight time windows (thus the time available for order picking becomes shorter). Many smaller warehouses are being replaced by fewer large warehouses to realise economies of scale. In these large warehouses, the daily pick volume is large and the available time window is short. In order to be more responsive to customers, many companies have adopted a postponement strategy (Van Hoek, 2001) leading to various value-adding activities (like kitting, labelling, product or order assembly, customised packaging or palletisation) that take place in the distribution centre and which have to be scheduled and integrated in the order-picking process. Warehouses are also involved in recovering products, materials, and product carriers from customers in order to redistribute them to other customers, recyclers, and original-equipment manufacturers (De Koster et al., 2002).

The organisation of order-picking operations immediately impacts the distribution centre’s and thereby the supply chain’s performance. Between the time an order is released to the warehouse and the time it takes to reach its destination, there is ample opportunity for errors in both accuracy and completeness, not to mention time lost. There is also room for improvement. Industry has come up with innovative solutions, making it possible to attain productivity up to 1000 picks per person hour. Science is also progressing rapidly. Over the last decades, many papers have appeared studying order picking processes. New problems have been studied and new models have been developed. Still, there is a gap between practice and academic research, since not all new picking methods have been studied and the optimal combinations of layout, storage assignment, order clustering, order release method, picker routing and order accumulation have been addressed to a minor extent only. This paper presents a systematic overview of these recent developments in academic literature. We structure typical decision problems in design and control of order-picking processes by focusing on optimal (internal) layout design, storage assignment methods, routing methods, order batching, and zoning. Several areas appear to have received only little attention from researchers. Innovations from practice also lead to new research challenges.

The remainder of the paper is organised as follows. In the next section, we briefly highlight warehouse missions and functions and give an overview of order-picking systems. In Sections 3 Layout design, 4 Storage assignment, 5 Zoning, 6 Batching, 7 Routing methods, 8 Order accumulation and sorting, we review recent literature on design and control of order-picking processes, focussing on layout design, storage assignment, batching, picker routing, and order accumulation. We conclude and discuss potential research directions in Section 8.

Section snippets

Warehouses and order picking

According to ELA/AT Kearney (2004), warehousing contributed to about 20% of the surveyed companies’ logistics costs in 2003 (other activities distinguished are value added services, administration, inventory costs, transportation and transport packaging). Warehouses apparently form an important part of a firm’s logistics system. They are commonly used for storing or buffering products (raw materials, goods-in-process, finished products) at and between points of origin and points of consumption.

Layout design

In the context of order picking, the layout design concerns two sub-problems: the layout of the facility containing the order-picking system and the layout within the order-picking system. The first problem is usually called the facility layout problem; it concerns the decision of where to locate various departments (receiving, picking, storage, sorting, and shipping, etc.). It is often carried out by taking into account the activity relationship between the departments. The common objective is

Storage assignment

Products need to be put into storage locations before they can be picked to fulfil customer orders. A storage assignment method is a set of rules which can be used to assign products to storage locations. Before such an assignment can be made, however, a decision must be made which pick activities will take place in which storage system.

Zoning

As an alternative to single order picking, the order picking area can be divided into zones. Each order picker is assigned to pick the part of the order that is in his assigned zone. Compared to other planning issues, the zoning problem has received little attention despite its important impact on the performance of order-picking systems. Possible advantages of zoning include the fact that each order picker only needs to traverse a smaller area, reduced traffic congestion, and furthermore the

Batching

When orders are fairly large, each order can be picked individually (i.e. one order per picking tour). This way of picking is often referred as the single order picking policy (or discrete picking or pick-by-order). However, when orders are small, there is a potential for reducing travel times by picking a set of orders in a single picking tour. Order batching is the method of grouping a set of orders into a number of sub-sets, each of which can then be retrieved by a single picking tour.

Routing methods

The objective of routing policies is to sequence the items on the pick list to ensure a good route through the warehouse. The problem of routing order pickers in a warehouse is actually a special case of the Travelling Salesman Problem, see also Lawler et al. (1995). The travelling salesman problem owes its name to the problem described by the following situation. A salesman, starting in his home city, has to visit a number of cities exactly once and return home. He knows the distance between

Order accumulation and sorting

When batching and/or zoning is applied, usually some additional effort is needed to split the batch and to consolidate the items per customer order or per destinations to which orders will be shipped. These processes are often called accumulation/sorting (A/S).

Fig. 9 shows an example of a typical A/S system (mentioned in Meller, 1997, Johnson, 1998). Items of a group of orders (a pick-wave) that are to be loaded onto a certain number of trucks are picked from the picking area. In general, items

Conclusions

We can draw the following conclusions from the literature. First, in spite of their dominance in practice, pickers-to-parts order-picking systems have received less research attention compared to parts-to-picker order-picking systems. Less than 30 percent of the about 140 papers we considered concerns pickers-to-part order-picking systems. The reasons for this may have something to do with the complexity and diversity of picker-to-parts order-picking systems. Furthermore, parts-to-picker

References (141)

  • D.R. Gibson et al.

    Order batching procedures

    European Journal of Operational Research

    (1992)
  • M. Goetschalckx et al.

    An efficient algorithm to cluster order picking items in a wide aisle

    Engineering Costs and Production Economy

    (1988)
  • M. Guenov et al.

    Zone shape in class based storage and multicommand order picking when storage/retrieval machines are used

    European Journal of Operational Research

    (1992)
  • C.M. Hsu et al.

    Batching orders in warehouses by minimizing travel distance with genetic algorithms

    Computers in Industry

    (2005)
  • H. Hwang et al.

    Order batching algorithms for a man-on-board automated storage and retrieval system

    Engineering Costs and Production Economics

    (1988)
  • C.C. Jane et al.

    A clustering algorithm for item assignment in a synchronized zone order picking system

    European Journal of Operational Research

    (2005)
  • T. Le-Duc et al.

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

    European Journal of Operational Research

    (2007)
  • C.M. Liu

    Clustering techniques for stock location and order-picking in a distribution center

    Computers and Operations Research

    (1999)
  • P.A. Makris et al.

    k-Interchange heuristic as an optimization procedure for material handling applications

    Applied Mathematical Modelling

    (2003)
  • C.J. Malmborg et al.

    A revised proof of optimality for the cube-per-order index rule for stored item location

    Applied Mathematical Modelling

    (1990)
  • J. Ashayeri et al.

    On the determination of class-based storage assignments in an AS/RS having two I/O locations

  • J.J. Bartholdi

    Balancing two-sided assembly lines: A case study

    International Journal of Production Research

    (1993)
  • Bartholdi, J., Eisenstein, D., 1996. Bucket brigades: A self-organizing order-picking system for a warehouse. Report,...
  • Bartholdi, J., Eisenstein, D., 2005a. Bucket brigades. Available on line at:...
  • J. Bartholdi et al.

    Using bucket brigades to migrate from craft manufacturing to assembly lines

    Manufacturing & Service Operations Management

    (2005)
  • Bartholdi, J.J., Hackman, S.T., 2005. Warehouse & distribution science. Available on line at:...
  • J. Bartholdi et al.

    Dynamics of two- and three-worker “bucket brigade” production lines

    Operations Research

    (1999)
  • J. Bartholdi et al.

    Performance of bucket brigades when work is stochastic

    Operations Research

    (2001)
  • Y. Bassan et al.

    Internal layout design of a warehouse

    AIIE Transactions

    (1980)
  • Y.A. Bozer et al.

    Throughput performance of automated storage/retrieval systems under stochastic demand

    IIE Transactions

    (2005)
  • Y.A. Bozer et al.

    An empirical evaluation of general purpose automated order accumulation and sortation system used in batch picking

    Material Flow

    (1985)
  • Y.A. Bozer et al.

    Travel-time models for automated storage/retrieval systems

    IIE Transactions

    (1984)
  • Y.A. Bozer et al.

    An evaluation of alternative control strategies and design issues for automated order accumulation and sortation systems

    Material Flow

    (1988)
  • F. Caron et al.

    Routing policies and COI-based storage policies in picker-to-part systems

    International Journal of Production Research

    (1998)
  • F. Caron et al.

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

    International Journal of Production Research

    (2000)
  • Choe, K., Sharp, G.P., 1991. Small parts order picking: design and operation. Available on-line at:...
  • Choe, K., Sharp, G.P., Serfozo, R.S., 1993. Aisle-based order pick systems with batching, zoning and sorting. In:...
  • G. Clarke et al.

    Scheduling of vehicles from a central depot to a number of delivery points

    Operations Research

    (1964)
  • Cormier, G., 1997. A brief survey of operations research models for warehouse design and operation. Report, Bulletin,...
  • G. Cornuéjols et al.

    The traveling salesman problem on a graph and some related integer polyhedra

    Mathematical Programming

    (1985)
  • R. Dekker et al.

    Improving order-picking response time at Ankor’s warehouse

    Interfaces

    (2004)
  • De Koster, R., 2004. How to assess a warehouse operation in a single tour. Report, RSM Erasmus University, the...
  • R. De Koster et al.

    Single-command travel time estimation and optimal rack design for a 3-dimensional compact AS/RS

  • R. De Koster et al.

    The Logistics of Supermarket Chains

    (2001)
  • R. De Koster et al.

    Routing orderpickers in a warehouse: A comparison between optimal and heuristic solutions

    IIE Transactions

    (1998)
  • R. De Koster et al.

    When to apply optimal or heuristic routing for orderpickers

  • R. De Koster et al.

    Reduction of walking time in the distribution center of De Bijenkorf

  • R. De Koster et al.

    Efficient orderbatching methods in warehouses

    International Journal of Production Research

    (1999)
  • R. De Koster et al.

    Return handling: An exploratory study with nine retailer warehouses

    International Journal of Retail & Distribution Management

    (2002)
  • Drury, J., 1988. Towards more efficient order picking. IMM Monograph No. 1, Report, The Institute of Materials...
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