Miranda-Ackerman M.A., Azzaro-Pantel C., Aguilar-Lasserre A.A., Bueno-Solano A., Arredondo-Soto K.C. (2019). Green supplier selection in the agro-food industry with contract farming: a multi-objective optimization approach. Sustainability, 01/12/2019, vol. 11, n. 24, p. 1-19.
https://doi.org/10.3390/su11247017
https://doi.org/10.3390/su11247017
Titre : | Green supplier selection in the agro-food industry with contract farming: a multi-objective optimization approach (2019) |
Auteurs : | M.A. Miranda-Ackerman ; C. Azzaro-Pantel ; A.A. Aguilar-Lasserre ; A. Bueno-Solano ; K.C. Arredondo-Soto |
Type de document : | Article |
Dans : | Sustainability (vol. 11, n. 24, December 2019) |
Article en page(s) : | p. 1-19 |
Langues : | Anglais |
Langues du résumé : | Anglais |
Catégories : |
Catégories principales 10 - INDUSTRIES ; 10.2 - IAA (en général)Thésaurus IAMM FOURNISSEUR ; AGRICULTURE CONTRACTUELLE ; SECTEUR AGROINDUSTRIEL ; METHODE D'OPTIMISATION ; ANALYSE DU CYCLE DE VIE ; CHAINE D'APPROVISIONNEMENT ; IMPACT SUR L'ENVIRONNEMENT ; PRATIQUE AGRICOLE ; MATIERE PREMIERE |
Résumé : | An important contribution to the environmental impact of agro-food supply chains is related to the agricultural technology and practices used in the fields during raw material production. This problem can be framed from the point of view of the Focal Company (FC) as a raw material Green Supplier Selection Problem (GSSP). This paper describes an extension of the GSSP methodology that integrates life cycle assessment, environmental collaborations, and contract farming in order to gain social and environmental benefits. In this approach, risk and gains are shared by both parties, as well as information related to agricultural practices through which the FC can optimize global performance by deciding which suppliers to contract, capacity and which practices to use at each supplying field in order to optimize economic performance and environmental impact. The FC provides the knowledge and technology needed by the supplier to reach these objectives via a contract farming scheme. A case study is developed in order to illustrate and a step-by-step methodology is described. A multi-objective optimization strategy based on Genetic Algorithms linked to a MCDM approach to the solution selection step is proposed. Scenarios of optimization of the selection process are studied to demonstrate the potential improvement gains in performance. |
Cote : | En ligne |
URL / DOI : | https://doi.org/10.3390/su11247017 |