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Addressing the Location Problem of a Perishables Redistribution Center in the Middle of Europe

This work aims to contribute to the debate on practical utilization of different location models for consolidation, redistribution, and repackaging centers in a supply chain to optimize shipments, thereby reducing food loss and waste, within the framework of quality of customer service improvement....

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Detalles Bibliográficos
Autores principales: Pérez-Mesa, Juan Carlos, Serrano-Arcos, M. Mar, Jiménez-Guerrero, José Felipe, Sánchez-Fernández, Raquel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8156944/
https://www.ncbi.nlm.nih.gov/pubmed/34069014
http://dx.doi.org/10.3390/foods10051091
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author Pérez-Mesa, Juan Carlos
Serrano-Arcos, M. Mar
Jiménez-Guerrero, José Felipe
Sánchez-Fernández, Raquel
author_facet Pérez-Mesa, Juan Carlos
Serrano-Arcos, M. Mar
Jiménez-Guerrero, José Felipe
Sánchez-Fernández, Raquel
author_sort Pérez-Mesa, Juan Carlos
collection PubMed
description This work aims to contribute to the debate on practical utilization of different location models for consolidation, redistribution, and repackaging centers in a supply chain to optimize shipments, thereby reducing food loss and waste, within the framework of quality of customer service improvement. The scenario in question is the creation of a redistribution center for highly perishable products (fruits and vegetables) from southeast Spain—the leading European supplier—for customers throughout Europe. It is estimated that 10% of exports (more than 530,000 metric tons) from this area are returned by customers due to minor defects. These products cannot be reused and are therefore wasted. Regarding the methodology, comparisons were made between the p-median, gravity p-median, and p-center models. Scenarios of change in demand and randomness in distances were also tested. In addition, the modelling used included the cost and time within a multicriteria optimization framework to assess the possibility of a transport mode change. It was observed, for example, that the gravity p-median model proved useful for perishable products and the logistics strategy chosen. Furthermore, the p-median model displayed strong robustness against long-term changes in demand and random distances. In general, it was demonstrated that this strategy would successfully reduce the response time and distance of shipment from the distribution center to the customers and thereby improve sustainability of the service, reducing the waste related to direct shipments. Furthermore, this research also demonstrated the difficulty of using intermodality in this context, mainly due to transit time, which would undoubtedly increase the waste generated.
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spelling pubmed-81569442021-05-28 Addressing the Location Problem of a Perishables Redistribution Center in the Middle of Europe Pérez-Mesa, Juan Carlos Serrano-Arcos, M. Mar Jiménez-Guerrero, José Felipe Sánchez-Fernández, Raquel Foods Article This work aims to contribute to the debate on practical utilization of different location models for consolidation, redistribution, and repackaging centers in a supply chain to optimize shipments, thereby reducing food loss and waste, within the framework of quality of customer service improvement. The scenario in question is the creation of a redistribution center for highly perishable products (fruits and vegetables) from southeast Spain—the leading European supplier—for customers throughout Europe. It is estimated that 10% of exports (more than 530,000 metric tons) from this area are returned by customers due to minor defects. These products cannot be reused and are therefore wasted. Regarding the methodology, comparisons were made between the p-median, gravity p-median, and p-center models. Scenarios of change in demand and randomness in distances were also tested. In addition, the modelling used included the cost and time within a multicriteria optimization framework to assess the possibility of a transport mode change. It was observed, for example, that the gravity p-median model proved useful for perishable products and the logistics strategy chosen. Furthermore, the p-median model displayed strong robustness against long-term changes in demand and random distances. In general, it was demonstrated that this strategy would successfully reduce the response time and distance of shipment from the distribution center to the customers and thereby improve sustainability of the service, reducing the waste related to direct shipments. Furthermore, this research also demonstrated the difficulty of using intermodality in this context, mainly due to transit time, which would undoubtedly increase the waste generated. MDPI 2021-05-14 /pmc/articles/PMC8156944/ /pubmed/34069014 http://dx.doi.org/10.3390/foods10051091 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pérez-Mesa, Juan Carlos
Serrano-Arcos, M. Mar
Jiménez-Guerrero, José Felipe
Sánchez-Fernández, Raquel
Addressing the Location Problem of a Perishables Redistribution Center in the Middle of Europe
title Addressing the Location Problem of a Perishables Redistribution Center in the Middle of Europe
title_full Addressing the Location Problem of a Perishables Redistribution Center in the Middle of Europe
title_fullStr Addressing the Location Problem of a Perishables Redistribution Center in the Middle of Europe
title_full_unstemmed Addressing the Location Problem of a Perishables Redistribution Center in the Middle of Europe
title_short Addressing the Location Problem of a Perishables Redistribution Center in the Middle of Europe
title_sort addressing the location problem of a perishables redistribution center in the middle of europe
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8156944/
https://www.ncbi.nlm.nih.gov/pubmed/34069014
http://dx.doi.org/10.3390/foods10051091
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