Invited Review
The forgotten sons: Warehousing systems for brick-and-mortar retail chains

https://doi.org/10.1016/j.ejor.2020.04.058Get rights and content

Highlights

  • We survey warehousing systems for brick-and-mortar retail chains.

  • The basic requirements are elaborated and compared to online retailing.

  • Each warehousing system is described, and the literature is summarized.

  • We identify important future research needs.

Abstract

Warehouses are an inevitable component in any supply chain and a vividly investigated object of research. Much attention, however, is absorbed by warehousing systems dedicated to the special needs of online retailers in the business-to-consumer segment. Due to the ever increasing sales volumes of e-commerce this focus seems self-evident, but a much larger fraction of retail sales are still realized by traditional brick-and-mortar stores. The special needs of warehouses servicing these stores are focused in this paper. While e-commerce warehouses face low-volume-high-mix picking orders, because private households tend to order just a few pieces per order from a large assortment, distribution centers of retail chains rather have to process high-volume-low-mix orders. We elaborate the basic requirements within both business segments and identify suited warehousing systems for brick-and-mortar stores (e.g., fully-automated case picking). The setup of each identified warehousing system is described, elementary decision problems are discussed, and the existing literature is surveyed. Furthermore, we identify future research needs.

Introduction

Warehousing, i.e., the intermediate storage of goods between stages in a supply chain (Bartholdi & Hackman, 2016), and its basic functions, i.e., receiving, storage, order picking, and shipping (Gu, Goetschalckx, & McGinnis, 2007), are inevitable in any supply chain. Therefore, it is not surprising that a vast body of literature on this topic has accumulated over the past decades (see the most recent surveys of Azadeh, de Koster, Roy, 2019, De Koster, Le-Duc, Roodbergen, 2007, Gu, Goetschalckx, McGinnis, 2007, Gu, Goetschalckx, McGinnis, 2010, Van Gils, Ramaekers, Caris, De Koster, 2018). A large part of this research effort – especially in recent years – is absorbed by warehousing systems dedicated to the special requirements of online retailers mainly in the business-to-consumer (B2C) segment (e.g., see the large body of literature reviewed in the survey of Boysen, De Koster, and Weidinger (2019b) on e-commerce warehouses). Due to the ever increasing sales volumes of e-commerce (Statista, 2018a) this focus seems self-evident, but a much larger fraction of retail sales are still realized by traditional brick-and-mortar stores. In spite of impressive growth rates, according to a recent estimate, the e-commerce share of total global retail sales will only reach 13.7% in 2019 (Statista, 2018b). The warehousing literature does not mirror this relation; literature specifically dedicated to warehouses servicing brick-and-mortar retail chains is (comparatively) rare. This survey paper intends to extenuate this bias. We review the scientific literature on warehouse operations fulfilling the demands of store-based retail chains and identify important future research needs.

The need for differently structured warehouses when either participating in e-commerce or servicing brick-and-mortar stores is mainly caused by deviating order characteristics. While online retailers face low-volume-high-mix picking orders, distribution centers for retail chains rather have to process high-volume-low-mix picking orders. In the B2C segment of online retailing, private customer households tend to order just a small number of products per order from a broad assortment, whereas brick-and-mortar stores offer a much smaller assortment in their restricted shop space, but typically order multiple pieces of each stock keeping unit (SKU). We detail the main requirements for warehouses servicing brick-and-mortar stores (in comparison to e-commerce) in Section 2, where we also identify suited warehousing systems that are able to satisfy (most of) the identified requirements. This defines the scope of our survey. Each of the identified warehousing systems (namely fully-automated case picking, pick-and-pass systems, crane-supplied pick faces, bulk picking, put systems, and picker-to-parts systems with vehicle support) is dedicated a separate section, where we describe the respective system, discuss the fit for the basic requirements, elaborate the main decision problems to be solved when setting up and operating such a specific warehousing system, and survey the existing literature. Finally, Section 9 concludes the paper.

Due to the great practical relevance of order fulfillment in the recent years, it is our impression that warehousing research revitalizes and many new researchers (are about to) enter this field. Therefore, our descriptions are intended general enough, so that OR researchers and practitioners not familiar with warehousing yet can understand the basic system setups, processes, decision problems, and future research needs. However, we hope that also established warehousing researchers receive a compact and concise (re-)introduction of warehousing systems that are not in the limelight of the warehousing literature.

Section snippets

Scope of survey: requirements and suited warehousing systems

Whether a warehousing system fits a specific application in an industry sector is mainly determined by the characteristics of customer orders that have to be processed. Note that, from the warehouse perspective, a customer does not need to be a final customer in the B2C sense, but can also be a sales outlet or a B2B customer. The specific order characteristics or requirements for warehousing systems that either service B2C online sales or brick-and-mortar stores are compared in Fig. 1 and

Fully-automated case picking

Fully-automated case picking is the only warehousing system surveyed in this paper where the complete order fulfillment process is automated. The assembly of mixed pallets or roll cages according to the orders of brick-and-mortar stores is executed by industrial robots. Current generation industrial robots are restricted to handling stable, rectangular and not-too-small products, so that SKUs not fulfilling these requirements have to be unified into cases, e.g., a dozen of milk cartons stacked

Pick-and-pass systems for large orders

The basic hardware element of a pick-and-pass system is a conveyor that transports, accompanied by a human picker, the order carriers (e.g., bins) in which customer orders are collected along the shelves of a fixed picking path. Different kinds of pick-and-pass systems exist, depending on the size of SKUs to be handled. The typical workstation for small-sized SKUs, such as pharmaceuticals, is depicted in Fig. 4(a). Here, the conveyor system is a simple unpowered roller-belt conveyor where the

Crane-supplied pick face

The basic element of a warehouse applying a crane-supplied pick face is a rack, which is subdivided into two parts: the bottom part is used as pick face and the upper as reserve area. The bottom row is the picking level where SKUs are directly accessible by human order pickers. Parallel to the pick face is a conveyor, e.g., an non-powered roller conveyor, on which bins or cardboard boxes associated with a store order accompany a human order picker along the pick face (step 1 of Fig. 5). The

Bulk picking and store consolidation

Bulk picking separates the order fulfillment process into three basic stages, retrieving SKUs from storage, inducting pieces onto a sorter, and order consolidation. When processing a wave of orders, i.e., a subset of the total order set jointly sorted in one consolidation run, unit loads of SKUs (typically bins) are successively retrieved either from a parts-to-picker system (ASRS, e.g., a crane-operated rack (Boysen, Boywitz, Weidinger, 2018a, Roodbergen, Vis, 2009), a carousel (Litvak &

Put systems

Put systems (also denoted as inverse order picking, put-to-light systems, or order distribution systems) invert the basic logic of picker-to-parts systems in general and pick-and-pass systems in particular. Traditionally, the SKUs are stored at fixed storage positions and human pickers successively visit selected positions while collecting the products defined on a pick list. In a put system, the SKUs are mobile while the carriers in which customer orders are collected remain stationary. Note

Picker-to-parts systems with vehicle support

In picker-to-parts systems, human order pickers successively visit the storage positions of the SKUs defined on their pick lists and return to a central depot once their respective pick list is complete. Here, the completed order is handed over to the shipping area and a new pick list is started. Since store orders are large, i.e., they typically contain multiple order lines each demanding multiple pieces, the capacity of an unsupported human picker alone is often not large enough to handle a

Future research needs and conclusion

Table 1 summarizes the papers for each warehousing system and decision problem. Note that we only count those papers specifically solving a decision problem for the warehousing system, and not all papers we refer to in the respective section (e.g., on related problems or survey papers). Further note that papers may occur multiple times of they treat multiple problems. This summary table reveals that many areas are barely investigated. Especially the storage assignment problems in all

CRediT authorship contribution statement

Nils Boysen: Conceptualization, Methodology, Investigation, Writing - review & editing. René de Koster: Conceptualization, Methodology, Investigation, Writing - review & editing. David Füßler: Conceptualization, Methodology, Investigation, Writing - review & editing.

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