In this paper, we analyze three traditional reorder policies, namely Economic Order Interval (EOI), Economic Order Quantity (EOQ) and (S,s), applied to 5 food products with different shelf-life characteristics. A particular attention is paid to fresh products with limited shelf-life, which represent 3 out of the 5 products examined, and to the suitability of applying the inventory management policies to those products. An ad hoc simulation model, reproducing a real 2-echelon supply chain, was developed under Microsoft ExcelTM and used to simulate the flow of the different products along the supply chain, according to the three reorder policies. From the simulation, the minimum cost setting is first derived for all policies, taking into account the total cost generated by each policy. Then, additional performance parameters (e.g., the throughput time of items along the supply chain) are computed and compared to the products constraints (e.g., the shelf-life), to assess the real suitability of implementing each policy to the products considered. Both the supply chain modeled and the products data are derived from a real scenario; thus, it is expected that our outcomes and guidelines are of practical usefulness to inventory managers, to optimize inventory management of perishable products.

Analysis and optimization of inventory management policies for perishable food products: a simulation study

Rinaldi M.;
2014

Abstract

In this paper, we analyze three traditional reorder policies, namely Economic Order Interval (EOI), Economic Order Quantity (EOQ) and (S,s), applied to 5 food products with different shelf-life characteristics. A particular attention is paid to fresh products with limited shelf-life, which represent 3 out of the 5 products examined, and to the suitability of applying the inventory management policies to those products. An ad hoc simulation model, reproducing a real 2-echelon supply chain, was developed under Microsoft ExcelTM and used to simulate the flow of the different products along the supply chain, according to the three reorder policies. From the simulation, the minimum cost setting is first derived for all policies, taking into account the total cost generated by each policy. Then, additional performance parameters (e.g., the throughput time of items along the supply chain) are computed and compared to the products constraints (e.g., the shelf-life), to assess the real suitability of implementing each policy to the products considered. Both the supply chain modeled and the products data are derived from a real scenario; thus, it is expected that our outcomes and guidelines are of practical usefulness to inventory managers, to optimize inventory management of perishable products.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/436154
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