| 总结: | In the literature, integrated inventory model has received a lot of attention.
Most previous works on this topic have been based on the assumption
of constant demand rate. However this assumption is not reliable in reality;
it is either increasing or decreasing with time.
In this thesis, we considered the model which consists of a single vendor
who manage the production and deliver to a single buyer with a linearly
decreasing demand rate over a finite time horizon. Costs are attached to
manufacturing set up, the delivery of a shipment and stockholding at the
vendor and buyer. The objective is to determine the number of shipments
and size of those shipments which minimize the total system cost - assuming
the vendor and buyer collaborate and find a way of sharing the consequent
benefits.
We begin this thesis with the integrated inventory policy for shipping a
vendor’s final production batch to a single buyer under linearly decreasing
demand. The first case considered here is the holding cost at the vendor is less
than at the buyer. We solve this model with equal shipment sizes policy, equal
shipment periods policy and unequal shipment sizes and unequal shipment
periods policy.
Then, we develop a mathematical model when the unit holding cost is higher at the vendor rather than at the buyer (consignment stock problem).
For this case, we also consider equal shipment sizes policy, equal shipment
periods policy, and unequal shipment sizes and unequal shipment periods as
in the previous case policy.
It is followed by an integrated inventory model with n production batches
which consists of the final batch at the end of the production cycle. This
model also considers the case of the buyer’s holding cost being greater than
the vendor’s and vice versa. We consider this model with equal cycle time
and unequal cycle time for both policies. We show the solution procedure
when the shipment sizes are equal and when they are unequal.
We solve all the models in this thesis using Microsoft Excel Solver and
illustrate all the policies with numerical examples and sensitivity analysis.
Then we make some comparison of the model. Lastly we end the thesis with
conclusion and some recommendations for further research.
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