Inventory Management Using Cross Prediction
Inventory management involves determining optimum inventory stock that should be held. It is necessary to introduce a set of policies and controls that establish and track levels of inventory and determine when stock should be refilled. At a firm level, identifying all opportunities for optimizing the value chain and lowering the warehouse cost is a main requirement for an efficient stock management. In this paper a supply chain application is modelled to support and optimize the stock management activity. This topic is addressed by using autoregressive method to model a supply chain application. Also, the potential of cross prediction is tested for increasing the performance of the auto regression method. SQL server Analysis services and visual basic for application is used for implementing the supply chain application.
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