In this paper, we analyse three traditional reorder policies, namely economic order interval (EOI), economic order quantity (EOQ) and (S, s), applied to five food products with different shelf-life characteristics; three fresh products with limited shelf-life are considered. An ad hoc simulation model, reproducing a real two-echelon supply chain, was developed under Microsoft ExcelTM to simulate the product flow along the supply chain, according to the three policies. From the simulation, the minimum cost setting is first derived for all policies. Then, additional performance parameters (e.g., the throughput time of items) are computed and compared with the products constraints (e.g., the shelf-life), to assess the real suitability of implementing each policy to the products considered. Because both the supply chain modelled and the products data are derived from a real scenario, our outcomes should be of practical usefulness to inventory managers, to optimise inventory management of perishable products. © 2014 Inderscience Enterprises Ltd.
Analysis and optimisation of inventory management policies for perishable food products: a simulation study
Rinaldi, Marta
2014
Abstract
In this paper, we analyse three traditional reorder policies, namely economic order interval (EOI), economic order quantity (EOQ) and (S, s), applied to five food products with different shelf-life characteristics; three fresh products with limited shelf-life are considered. An ad hoc simulation model, reproducing a real two-echelon supply chain, was developed under Microsoft ExcelTM to simulate the product flow along the supply chain, according to the three policies. From the simulation, the minimum cost setting is first derived for all policies. Then, additional performance parameters (e.g., the throughput time of items) are computed and compared with the products constraints (e.g., the shelf-life), to assess the real suitability of implementing each policy to the products considered. Because both the supply chain modelled and the products data are derived from a real scenario, our outcomes should be of practical usefulness to inventory managers, to optimise inventory management of perishable products. © 2014 Inderscience Enterprises Ltd.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.