an aggregated newsvendor model for multi-item perishable inventories with uncertain demand

In industrial and commercial settings, inventory systems often involve managing multiple products with diverse demand patterns, making the direct application of the single-item newsvendor model inefficient. to address this complexity, this study proposes an adaptation of the newsvendor model through demand aggregation, where related items are grouped into a product family. by aggregating demand and financial parameters, the traditional newsvendor approach can be extended to multi-item systems, simplifying the inventory management process. this method was tested in two different case studies—a coffee roaster company and a meatball producer—demonstrating its validity and applicability. the aggregated newsvendor model was found to enhance inventory accuracy and efficiency, reducing random error and improving operational performance. this approach offers a valuable extension of the newsvendor model, with potential for broader application across various industries.