R. de Feijter
Operational procedures for order picking
Report 99.3.LT.5258, Transport Technology, Logistic Engineering.
Warehousing involves all movement of goods within a warehouse. These
movements are affected by management decisions. Management decisions
within a warehouse can be divided into three categories:
The control of warehousing operations covers the following decision types
on the operational level:
- Strategic decisions;
- Tactical decisions;
- Operational decisions.
Closely related to these decision types on the operational level are some
decision types on the tactical and strategic level:
- Batching / Splitting up of orders;
- Routing and sequencing;
- Dwell point positioning.
The layout of a warehouse (in this context: The way in which storage and
retrieval are organized) can be subdivided into:
- Layout of the warehouse (strategic level);
- Storage location planning (tactical level).
The part-to-picker systems can be subdivided into systems performing
single command cycles, systems performing dual command cycles, systems
performing multi command cycles or carousel systems. Picker-to-part
systems are always multi command cycle systems. Single command cycles
perform one storage or retrieval per cycle. Dual command systems perform
one storage and one retrieval per cycle. Multi command systems perform
multiple storages or retrievals per cycle.
- Picker-to-part systems;
- Part-to-picker systems;
- Picker-less systems.
Single command systems do not need batching or sequencing methods. The
dwell-point is preferably dynamically located at the location that minimizes
the expected S/R-machine travel time from the dwell point to the points of
need. In most situations the input location is also a good location for the
dwell-point. The storage policy can be dedicated, class-based or random. In
balanced systems the duration-of-stay based dedicated policy prevails, whereas
in other systems the turnover (or cube-per-order index) based class policy
provides better results.
Dual command systems, like single command systems, do not need batching
methods. Sequencing methods are used to determine the best way to combine a
storage and a retrieval request. In most systems this means choosing a
retrieval request from a list to link it to a given storage request, because
the storage requests have to be performed in a first-come-first-serve manner.
The optimal dwell-point location in a dual command cycle is the input point.
This is especially true when all performed cycles are dual command cycles. As
for most single command systems, the best storage policy for dual command
cycles is the turnover based class policy.
In multi command part-to-picker systems, most batching methods are composed of
two major parts: the seed selection rule and the additon rule. There are many
alternatives for both rules. When creating a batch, including all assigned
orders in the seed provides better results than keeping the original seed. An
order batching rule which uses the economic convex hull in the seed selection
and in the order addition rule shows the best results. Routing / sequencing
heuristics try to determine a minimal tour passing through all the locations
that have to be visited. Some possible heuristics are the nearest-neighbour,
spacefilling curve, ½-band insertion and the hull heuristic. The best
performing heuristic is the hull heuristic. The results of this heuristic can
be further improved by an improvement algorithm.
The desirable dwell-point position and the storage policy are the same as in
the case of a dual command cycle. The class-boundaries however do not have to
be L-shaped as in the case of a dual command system.
The construction of most batching algorithms for a multi command picker-to-part
system uses the same basic rules as a part-to-picker system: the seed-selection
rule and the order addition rule. An order batching algorithm which uses a
minimum additional aisle method in the seed selection rule and in the order
addition rule provides the best results in this situation.
The routing of the order picking tour can use a traversal, a return policy or a
combination of both. This tour can either be created by a heuristic or optimally
determined. A well performing method, especially when multiple cross-aisles are
present, is a heuristic that uses a combination of both policies. When the
aisles are wider, the largest gap method (return policy) tends to become more
The desirable dwell-point position and the storage policy are once again the
same. If the orders are picked in a traversal manner, the A-zone (as in
ABC-curve) covers the aisles closest to the I/O-point. However, if the orders
are picked in a return manner, the A-zone covers the outer end(s) of the
In carousel systems, the batching of orders can be done with simple algorithms
because the distance between the locations is one-dimensional. The sequencing of
orders in a carousel system has a special property (a cycle can stop at any
position) that provides an opportunity to increase the efficiency of the system.
An algoritm called Matchtree effectively performs this task.
When the random storage policy is used, the dwell point can be arbitrarily
chosen. The class-based storage policy is, again, the most promising.
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