An evaluation of routing and volume-based storage policies in an order picking operation

Decision Sciences, Spring 1999 by Petersen, Charles G II, Schmenner, Roger W

ABSTRACT

Order picking, the assembly of a customer's order from items in storage, is an essential link in the supply chain and is the major cost component of warehousing. The critical issue is to simultaneously reduce the cost and increase the speed of the order picking activity. This study departs from the limited prior research that focused on either routing of workers or storage of warehoused items. The main objectives are to (1) evaluate various routing heuristics versus an optimal routine in a volume-based storage environment, (2) propose several methods of implementing volume-based storage, and (3) examine the interaction of the routing and storage policies under different operating conditions of pick list size and demand skewness. The experimental results show statistically significant differences in the mean route distance for the routing policies, storage policies, and their interactions. Further testing indicates that the choice of certain routing and storage policies in combination can result in increased picking efficiency.

Subject Areas: Distribution/Logistics and Heuristics.

INTRODUCTION

Order picking is the retrieval of items from their warehouse storage locations to satisfy independent customer orders. It is an important link in the supply chain, constituting 65% of the total operating costs for a typical warehouse (Coyle, Bardi, & Langley, 1996). The critical issue in today's business environment is to simultaneously reduce the cost and increase the speed of order picking.

Although order picking appears to be a relatively simple function to perform, it is done in several different ways by different companies. There are two major policy decisions that determine the efficiency of order picking operations: (1) storage policies and (2) routing policies.

1. Storage policies assign items to storage locations. Items may be assigned randomly, similar items may be grouped in the same area of the warehouse, or items may be assigned based on order or picking volume. Volume-based storage places high volume items close to the pick-up/drop-off (P/D) point to minimize picker travel. Volume-based storage is particularly noteworthy as it results in less picker travel (Coyle et al., 1996; Sims, 1991). It is for this reason that this paper concentrates on volume-based storage. Nevertheless, there are many warehouses that, in practice, employ random storage, or that identify relatively few items for volumebased storage. A goal of this paper is to underscore the benefits of volumebased storage and how it can be accomplished.

2. Routing policies determine the route of a picker for a picking tour, specifically the sequence in which items are to be picked. These policies could include either simple heuristics or optimal procedures.

Previous Research

This paper investigates several procedures for routing pickers in a warehouse and various methods of storing warehoused items. Previous research has focused on either routing or storage, but this paper breaks new ground by examining the interaction of routing and storage policies. In particular, no study has compared the performance of routing heuristics to the optimal in a volume-based storage environment. In addition, various methods of implementing volume-based storage are investigated, and the interaction of these storage policies with routing policies is examined.

The literature on order picking has focused on either routing or storage policies. Ratliff and Rosenthal (1983) and Goetschalckx and Ratliff (1988a,1988b) have developed optimal algorithms for routing pickers in a rectangular warehouse. In addition, Elsayed (1981) and Elsayed and Stern (1983) investigated the assignment of picks to pickers and the routing of the pickers in an automated storage/retrieval system. However, this paper focuses on heuristics in the more prevalent manual warehouse. Hall (1993) examined routing heuristics in a manual warehouse. In addition, Hall developed distance approximations for several routing heuristics in a random storage warehouse and investigated the impact of warehouse shape.

Schwarz, Graves, and Hausman (1978) examined the performance of an automated warehouse with random and volume-based storage. In addition, Gibson and Sharp (1992) and Gray, Karmarkar, and Seidmann (1992) found that locating high volume items close to the P/D point results in a significant increase in picking efficiency. However, they did not provide information on the precise mechanism of volume-based storage. Jarvis and McDowell (1991) stated that the optimal storage strategy is to place the most frequently picked items in the aisle nearest the P/ D point and the next most frequently picked items in the next aisle. This research was limited in that it assumed that the aisles only allowed one-way travel.

Although the prior research has made some important contributions to the understanding of order picking, several issues still need to be addressed. First, no one has evaluated routing heuristics in a volume-based environment. Second, little research (Jarvis & McDowell, 1991; Schwarz et al., 1978) has been done to develop volume-based storage implementation strategies. Third, only a few studies (Hall, 1993; Schwarz et al.) have investigated the interaction between routing policies, storage policies, and/or different operating conditions.