Cataloged from PDF version of article.Quick response mechanisms based on effective use of up-to-date demand information help retailers to
reduce their inventory management costs. We formulate a single-period inventory model for multiple
products with dependent (multivariate normal) demand distributions and a given overall procurement
budget. After placing orders based on an initial demand forecast, new market information is gathered
and demand forecast is updated. Using this more accurate second forecast, the retailer decides the total
stocking level for the selling season. The second order is based on an improved demand forecast, but it
also involves a higher unit supply cost. To determine the optimal ordering policy, we use a
computational procedure that entails solving capacitated multi-item newsboy problems embedded
within a dynamic programming model. Various numerical examples illustrate the effects of demand
variability and financial constraint on the optimal policy. It is found that existence of a budget
constraint may lead to an increase in the initial order size. It is also observed that as the budget
available decreases, the products with more predictable demand make up a larger share of the
procurement expenditure.
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