Evaluating lateral transshipment policy in a two-echelon inventory system.
Satyendra, Kumar ; Venkata, Rao V.
Emergency shipments from higher and/or same echelon levels are one
of the popular tools to handle the stock-out position at some warehouse.
Our paper deals with a lateral stock transshipment model involving one
plant and two warehouses, lateral transshipment is considered as an
option at each re-order decision under the standard (r,Q) inventory
replenishment policy. We focus on incorporating the above stock transfer
feature in the order fulfillment decision and designed an simulation to
find the effect of lateral stock transfer policy on various parameters
viz. average inventory at each warehouse, average number of stock-out
days at each warehouse, total cost (comprising of inventory cost,
stock-out cost and transportation cost). The experimental results show
that the stock transfer policy has the potential to reduce the total
cost, average inventory and average stock-out days. We have also
compared the cases where information is shared online or with some
delay. The delay is because of serial communication between the supply
chain players. The results show that there are benefits of no
information delay i.e. online information sharing over the case with
information delay.
Introduction
One of the key issues in multiple retailer inventory system, where
each retailer is facing random demand, is to handle the stock-out
position at one retailer when there is inventory at other retailer. This
situation can be resolved either by emergency order to the higher
echelon or lateral transshipment from other retailer having inventory to
spare. Companies are utilizing emergency lateral transshipments between
retailers to meet customer demand to improve service levels and / or
reduce costs [Minner et al. (2003)]. The savings in the expected lost
sales and inventory costs at the retailers may balance the excess cost
of lateral transshipment [Robinson (1990)]. The other issue of lateral
transshipment is to figure out the factors influencing the lateral
transshipment and its impact on system performance levers (2001)].
Recently, Hong-Minh et al. (2000) compared emergency lateral
transshipment policy with different strategies for improving customer
service. The strategies considers are: EPOS (marketplace information is
shared between supply chain players), Excel (stock levels in all
locations are centrally controlled), emergency transshipments
(transportation route bypassing an echelon), and eliminate (an echelon
is removed from the supply chain). They evaluated the strategies by
simulation exercise and found that emergency transshipments has a strong
impact on customer service level and eliminate results in less stock for
an improved customer service level.
The common point in all the earlier studies including Das (1975),
Lee (1987), Axsater (2003), etc. is that the lateral transshipment is
allowed only in case of stock-out situations, i.e. during emergencies.
Some of the selected research studies dealing with lateral transshipment
are presented in table 1. In the present study, we try to analyze a
continuous-review inventory system, which allows lateral transshipments
as a regular inventory policy. Our study dealt with the following
questions: under what conditions is it advisable for a warehouse to
transfer the stock to another warehouse, when both warehouses originally
get their orders replenished only from the central plant and how the
different parameters will affect the system performance. We confine our
study to one plant and two warehouse system, and focus on incorporating
the above stock transfer feature in the order fulfillment decision, when
both warehouses follow an (r, Q) inventory policy.
Methodology
This research is motivated by a multi-product manufacturing
company, which has three manufacturing units located in the western
region of India and the regional warehouses are located all over the
country. The company deals with a variety of products and they often
face stock-out situation even at manufacturing units because of large
number of product groups and high demand variability. The facilities
(corporate office / manufacturing complexes / regional offices) are
interconnected by an integrated system for online information sharing.
The concerned business groups of corporate office mainly do the
production and distribution planning for various products. The shipment
to the regional warehouses is done in full truckloads, each truck
containing only a single product. However, smaller trucks are used for
lateral shipments.
Based on above salient points, we have designed a simulation model
to assess the impact of stock transfer within same echelon on
transportation, inventory, and stock-out costs and the service level. We
have considered a single manufacturing unit and two regional warehouses,
which are relatively close to each other compared to the manufacturing
unit. We have considered a single product and generated the daily demand
(normally distributed) for the two regional warehouses. Each warehouse
for stock replenishment follows (r, Q) policy, where 'r' is
the reorder level and 'Q' is the replenishment quantity. The
demand experienced by a regional warehouse is fulfilled from its
existing stock. In the absence of the stock, orders received by a
regional warehouse are lost and stock-out cost is incurred. When the on
hand inventory quantity at a warehouse reaches its reorder point, a
replenishment order is placed as per the following two cases:
Case 1: A stock replenishment order by a warehouse is placed on the
manufacturing unit. The order is fulfilled immediately if the plant
warehouse has stock on hand; otherwise, the order waits until the
product is produced. Case 2: When the on-hand inventory quantity at a
warehouse reaches its reorder point, the stock level at other regional
warehouse is checked. If the stock level of other warehouse is more than
a predetermined threshold level (the stock level above which the stock
can be transferred from one warehouse to another warehouse), the order
is placed on to the other warehouse. The predetermined quantity is
dispatched immediately. In the absence of excess stock at the other
warehouse, the order is placed on to the manufacturing unit. The order
is dispatched immediately if there is available stock at plant premises
otherwise the order waits till the production occurs. The conceptual
model is presented in figure 1. The difference between the two cases is
the stock transfer linkage between the two warehouses.
The following figure explains the replenishment process.
[FIGURE 1 OMITTED]
Simulation Design
We have designed a simulation to find the effect of lateral stock
transfer policy on various parameters viz. average inventory at each
warehouse, average number of stock-out days at each warehouse, total
cost (comprising of inventory cost, stock-out cost and transportation
cost). The number of days in each simulation run is 300 and the daily
demand is generated for each warehouse. We have first checked the
robustness of the simulation design. We have taken each output parameter separately and observed the mean value after each simulation run. We
observed that the coefficient of variation of the output value falls
below 0.1 after 12-15 runs. In addition, after 20 run the mean of the
output value almost stabilizes. Based on these observations, we
conducted our experiment with each run consisting of 300 days, the total
number of runs being 25 for each experiment.
Experiments and Results
We have designed and performed various experiments to analyze the
impact of lateral stock transfer policy. In a typical experiment, we
have considered:
* Time period as 300 days. The demand for each warehouse is
generated for this time period.
* The unit of the product is 20 KG, which costs approximately Rs.
1000.
* The plant production period is bimonthly and the maximum
production level is 4000 units.
* The under-stocking cost can be considered as the loss of
contribution and will be approximately Rs. 50.
* The overstocking cost includes the inventory holding cost,
pilferage cost and other warehouse costs and will be approximately Rs 1
per unit per day.
* The vehicle used to carry material from the manufacturing unit to
the regional warehouse has a capacity of 20 MT i.e. 1000 units. Thus,
the replenishment quantity 'Q' is 1000 units.
* The lateral transshipment is performed by small canters having
capacity of 4 / 5 MT, which is equivalent to 200 / 250 units of product.
Thus, the lateral shipment quantity is 200 / 250 units.
* The predetermined threshold level and reorder level are
considered to percentage of replenishment quantity 'Q'. Thus,
the transfer 70% means that the lateral transfer will happen only when
the stock at the warehouse is more than 70% of replenishment quantity
'Q' i.e. 700 units. Similarly, 20% reorder level means reorder
level is 20% of replenishment quantity 'Q' i.e. 200 units.
We have generated various test problems by varying the
transportation cost, transit time and demand distribution parameters.
For each test problem, we have varied the reorder level and threshold
stock level and run 25 instances. For each instance, we have recorded
various outputs viz. total cost, average inventory and average number of
stock-out days. Some of these results have been plotted to discuss the
trends.
We have also performed experiments to analyze the situation when
the lateral shipment from only warehouse rather than from both
warehouses. We have assumed the transit time of the two warehouses from
the manufacturing unit to be 8 and 10 days. The warehouse with transit
time of 8 days can only transfer the stock to other warehouse.
[FIGURE OMITTED]
From the graphs, it can be observed that
* The curves show that the average stock-out days in case of stock
transfer are less than no stock transfer case for almost all reorder
levels.
* In case of no transfer, the average stock-out days shows the
downward trend with increasing reorder level, which is obvious. But, in
case of stock transfer, the average stock-out days first decreases and
then increases with increasing reorder level. It is because at high
reorder level, the lateral transshipments are frequent and thus the
other warehouse faces stock-out conditions.
* At high reorder level [40%], the no stock transfer policy seems
to be better than the stock transfer policy as the warehouses keeps
enough safety stocks to deal with uncertainty and the lateral
transshipment only adds to the transportation cost. Moreover, the
objective of stock transfer policy to enhance the service level even by
maintaining lower stock level is not met at higher reorder levels.
* For some parameter values, the stock transfer from single
warehouse is beneficial than that of both warehouses performing lateral
transshipment.
Benefit of Information Sharing
We have also compared the cases where there is no information delay
and information delay of 1 and 2 days. The delay is because of serial
communication once the reorder level is reached at one warehouse. The
results show that the benefit of no information delay i.e. online
information sharing over cases with information delay of 1 day is
approximately 2%.
[FIGURE OMITTED]
Sensitivity Analysis
The performance of the stock transfer policy depends mainly on
three parameters i.e. re-order level, threshold level, and lateral
shipment quantity. We have designed experiments to find the sensitivity
of these three parameters. We have varied reorder level, threshold level
and lateral shipment quantity, and computed the total cost for various
input combinations. From the results, we have figured out that the
reorder level is the most sensitive parameter. In addition, at every
reorder level, the combination of threshold level and lateral shipment
quantity also plays a very important role in overall policy performance.
[FIGURE OMITTED]
Inferences
From the representative results, we have the following inferences:
* The stock transfer policy has the potential to reduce the total
cost, average inventory and average stock-out days by approximately 45%.
* The result shows that the benefit of no information delay i.e.
online information sharing over the case with information delay is
approximately 2%.
* The stock transfer policy can maintain a similar service level
and reduces the total cost at lower inventory level i.e. reorder level.
* There were situations where stock transfer from only one
warehouse is beneficial instead of stock transfer from both the
warehouses.
The managerial implications of this simulation model are as
follows:
* The simulation model solves for various reorder level and stock
transfer level to identify the best inventory policy for a given set of
parameters.
* From the sensitivity analysis, one can figure out the parameter
with maximum variations.
* The impact of various parameters can also be analyzed and based
on the criticality it can be taken care.
* Based on the experiments, the inventory policy can be analyzed
and implemented.
Conclusion
The idea of warehouses directly replenishing one another has
potential to reduce costs in inventory management .The existing
literature has analyzed the lateral stock transfer policy in two major
cases viz. emergency transshipment and after fixed time-period. The
present study is different in that it is not concerned with emergency
transshipments, but with considering lateral stock transfer at every
re-ordering event. Our model shows that the stock transfer policy has
the potential to reduce the total cost, average inventory and average
stock-out days by approximately 4-5%. The results obviously are limited
to the values of the parameters used in the experiments. Further
research can be undertaken to extend the ideas of this paper in two
different directions: 1) An understanding of the general relationship
between the optimal value of the objective function and the parameters
of interest, 2) Analysis of a system consisting of several plants and
several warehouses.
References
Alfredsson, P., and Jos V., "Modeling emergency supply
flexibility in a two-echelon inventory system," Management Science,
Volume 46, Issue 10, pp. 1416-1431, 1999.
Archibald, T. W., Sassen S. A. E., and Thomas L. C., "An
optimal policy for a two depot inventory problem with stock
transfer," Management Science, Volume 43, Issue 2, pp. 173-183,
1997.
Axsater, S., "Modeling emergency lateral transshipments in
inventory systems," Management Science, Volume 36, Issue 11, pp.
1329-1338, 1990.
Axsater, S., "Evaluation of unidirectional lateral
transshipments and substitutions in inventory systems," European
Journal of Operational Research, Volume 149, Issue 2, pp. 438-447, 2003.
Das, C., "Supply and redistribution rules for two-location
inventory systems: One-period analysis," Management Science, Volume
21, Issue 7, pp. 765-776, 1975.
Evers, P. T., "Heuristics for assessing emergency
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129, Issue 2, pp. 311-316, 2001.
Hong-Minh, S. M., Disney S. M., and Naim M. M., "The dynamics
of emergency transshipment supply chains," International Journal of
Physical Distribution and Logistics Management, Volume 30, Issue 9, pp.
788-816, 2000.
Lee, H. L., "A multi-echelon inventory model for repairable
items with emergency lateral transshipments," Management Science,
Volume 33, Issue 10, pp. 1302-1316, 1987.
Minner, S., Silver E. A., and Robb D. J., "An improved
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Kumar Satyendra
Functional Architect, Manugistics India Software Systems Ltd.,
India
Rao V. Venkata
Indian Institute of Management, Ahmedabad, India
Table 1: Topology of lateral transshipment research
Author Issue addressed
Das (1975) A periodic review stochastic
inventory model with
two-location, which allows
lateral stock transfer after
predetermined time within the
Lee (1987) period
A continuous review
multiechelon inventory model
for repairable items that
allows emergency lateral
Robinson (1990) shipment between the retailers
Total cost of optimal ordering
policy that allows lateral
stock transfer.
Transshipments are performed
Axsater (1990) after demands are
realized but not fulfilled.
A continuous review inventory
system with Poisson
Archibald demand and one-to-one
et al. (1997) replenishment, which allows
lateral transshipment
An optimal policy and its
parameters for UK based cart
part retailers. In case of
Alfredsson et stock-out either the lateral
al. (1999) shipment is done or emergency
order is placed.
A two-echelon inventory
system for service parts,
Evers (2001) allowing lateral
transshipments and
direct deliveries
in case of emergency.
Axsater (2003)
Evers (2001) Emergency transshipments
to solve shortages and
excess inventory situations
at multiple locations
Axsater (2003) An emergency lateral
transshipment policy, when
the warehouses have different
shortages cost.
Author Solution methodology Comments
Das (1975) Convex programming to The optimal conditions
solve total expected for a base stock
cost. conserving transfer
rules are established.
Lee (1987) A mathematical model Inter-retailer distance
is used to calculate is less than retailer-
expected backorder levels depot distance, thus
and quantity of lateral lateral shipment improves
stock transfer service level
Robinson (1990) Heuristic solution Analytical solution for
utilizing Monte-Carlo two special cases: only
integration. two retailer system or
cost parameters for all
retailers are similar
Axsater (1990) A mathematical model The work has been
using Little's formula extended to two-echelon
and properties of system of repairable
Poisson distribution items
Archibald Modeled the transfer Two retailers form a
et al. (1997) problem as a finite group and lateral
horizon continuous time movement is allowed only
Markov decision model between group members.
and used dynamic
programming to solve.
Alfredsson et A mathematical model The performance of the
al. (1999) to calculate parameters inventory system is
for performance measure. insensitive to the
A simulation exercise lead-time distribution.
to validate the findings.
Evers (2001) Heuristic technique to Discussed the factors
determine when lateral affecting lateral stock
transfer be performed transfer
Axsater (2003) A simulation study The system is also
interpreted as inventory
substitution.