We consider coordination among stocking locations through replenishment strategies that explicitly take
into account lateral transshipments, i.e., transfer of a product among locations at the same echelon level.
Our basic contribution is the incorporation of supply capacity into the traditional transshipment model.
Our goal is to analyze the impact on system behavior and on stocking locations’ performance of the fact
that the supplier may fail to fulfill all the replenishment orders. We therefore formulate the capacitated
supply scenario as a network flow problem embedded in a stochastic optimization problem, which is
solved through a sample average approximation method. We find that, depending on the production
capacity, system behavior can vary drastically. Moreover, in a production-inventory system, we find evidence
that either capacity flexibility (i.e., extra production) or transshipment flexibility (i.e., pooling) is
required to maintain a desired level of service.
We consider coordination among stocking locations through replenishment strategies that explicitly takeinto account lateral transshipments, i.e., transfer of a product among locations at the same echelon level.Our basic contribution is the incorporation of supply capacity into the traditional transshipment model.Our goal is to analyze the impact on system behavior and on stocking locations’ performance of the factthat the supplier may fail to fulfill all the replenishment orders. We therefore formulate the capacitatedsupply scenario as a network flow problem embedded in a stochastic optimization problem, which issolved through a sample average approximation method. We find that, depending on the productioncapacity, system behavior can vary drastically. Moreover, in a production-inventory system, we find evidencethat either capacity flexibility (i.e., extra production) or transshipment flexibility (i.e., pooling) isrequired to maintain a desired level of service.
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