Class-based storage policies divide items into classes and assign
a fixed area to each class and then use randomized storage allocation
within each class area. Bynzer and Johansson (1996) provided
a storage assignment strategy emanating from the product structure
to shorten the picking time by using variant characteristics
as picking information in the construction of a logical assignment
policy. Eynan and Rosenblatt (1994) developed an algorithm
involving a one-dimensional search for deriving the boundaries
for any desired number of classes in an automated warehouse. Results
show that this one-dimensional search procedure is very
effective in solving most practical problems.
Schwarz, Graves, and Hausman (1978) inspected the performance
of an automatic warehouse system through a specific storage
policy that depends on item picking frequency. Hsieh and Tsai
(2001) presented a bill of material (BOM) oriented class-based
storage assignment method for an automated storage/retrieval
system (AS/RS). The proposed method possesses not only the
advantage of a class-based storage method, but also the feasibility
to integrate an AS/RS into a computer integrated manufacturing
(CIM) system. Larson, March, and Kusiak (1997) presented a procedure
for warehouse layout by employing the principles of classbased
storage to increase floor space utilization and reduce material
handling efforts.
Petersen and Gerald (2004) analyzed the effects of picking, storage
and routing decisions on order picker traveling and concluded
that the use of either a class-based or volume-based storage policy
provides nearly the same level of savings as batching consideration.
Gibson and Sharp (1992) demonstrated that significant
reductions in distance can be achieved through locating high frequency
items close to the I/O point. Ruben and Jacobs (1999)
developed batch construction heuristics and found that the methods
used for constructing batches of orders and for assigning storage
space to individual items have significantly impact on order
retrieval efforts in a warehouse.
Most previous research studied the storage policy for AS/RS or
picker-to-part systems while few considered the pick-and-pass
systems. An order picking line can be divided into several zones
and each zone is assigned a picker in it. After finishing the pickings
in the zone, the picker hands the container with picked items to
the next picker, who continues the assembly of the order. Therefore
an order is only finished after having visited all relevant zones.
This system is referred to as a pick-and-pass system (De Koster, Le-
Duc, & Roodbergen, 2007). In general, such a system stores small to
medium-sized items such as health and beauty, household, office
or food products (Maloney, 2000).
For pick-and-pass systems, De Koster (1994) developed an
approximation method to evaluate the effect of changing the layout
of the system. Malmborg (1995) studied the problem of assigning
products to locations with zoning constraints. Jane (2000)