Treffer: Managing quality, supplier selection, and cold‐storage contracts in agrifood supply chain through stochastic optimization.

Title:
Managing quality, supplier selection, and cold‐storage contracts in agrifood supply chain through stochastic optimization.
Authors:
Mateo‐Fornés, Jordi1 (AUTHOR) jordi.mateo@udl.cat, Soto‐Silva, Wladimir2 (AUTHOR) wsoto@ucm.cl, González‐Araya, Marcela C.3 (AUTHOR) mgonzalez@utalca.cl, Plà‐Aragonès, Lluís M.4,5 (AUTHOR) lluismiquel.pla@udl.cat, Solsona‐Tehas, Francesc1 (AUTHOR) francesc@diei.udl.cat
Source:
International Transactions in Operational Research. Jul2023, Vol. 30 Issue 4, p1901-1930. 30p. 5 Diagrams, 8 Charts, 1 Graph.
Database:
Business Source Premier

Weitere Informationen

The quality of such processed agrifood products as dehydrated apple is related to the quality and variety of fresh harvested products and connected with wastage reduction throughout the agrifood supply chain. For this purpose, cold‐storage management is important to avoid or mitigate the quality decay of fresh products stored in refrigerated systems. This paper explores the benefits of a two‐stage stochastic programming model for product quality through the selection of producers and the management of cold storage to mitigate deterioration and guarantee the maintenance of quality. A case study with real data from an agribusiness company is presented in the case study to illustrate and assess the suitability of the stochastic approach. Uncertainty regarding the conversion rate of fresh apples into the final dehydrated product and the purchase cost of the apples in the system are represented through scenarios generated from historical data. Recourse actions include the purchase of additional fruit and renting of additional cold stores to meet the demand. Based on the different scenarios, the value of the stochastic solution shows that modeling and solving the proposed stochastic model minimizes costs by an average of around 6.4%. In addition, the expected value of perfect information demonstrates that using a proactive strategy could reduce costs by up to 9%. These results ensure the applicability of this model in practice before and during the harvesting season for planning and replanning as uncertainty is revealed under a rolling horizon. [ABSTRACT FROM AUTHOR]

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