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Collaborative Plan to Reduce Inequalities Among the Farms through Optimization

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Collaborative Plan to Reduce Inequalities Among the Farms through Optimization

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Esteso, A.; Alemany Díaz, MDM.; Ortiz Bas, Á.; Iannacone, R. (2021). Collaborative Plan to Reduce Inequalities Among the Farms through Optimization. IFIP Advances in Information and Communication Technology. 629:125-137. https://doi.org/10.1007/978-3-030-85969-5_11

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/188314

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Título: Collaborative Plan to Reduce Inequalities Among the Farms through Optimization
Autor: Esteso, Ana Alemany Díaz, María Del Mar Ortiz Bas, Ángel Iannacone, Rina
Entidad UPV: Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses
Fecha difusión:
Resumen:
[EN] The crop planning problem consists in defining the crop and acreage to be planted at each farm. There are several centralized mathematical programming models to support crop planning in literature. However, centralized ...[+]
Palabras clave: Agri-food supply chain , Crop planning , Collaboration , Optimization
Derechos de uso: Reserva de todos los derechos
Fuente:
IFIP Advances in Information and Communication Technology. (issn: 1868-4238 )
DOI: 10.1007/978-3-030-85969-5_11
Editorial:
Springer
Versión del editor: https://doi.org/10.1007/978-3-030-85969-5_11
Serie: IFIP Advances in Information and Communication Technology
Código del Proyecto:
info:eu-repo/grantAgreement/EC/H2020/691249/EU
Agradecimientos:
We acknowledge the support of the project 691249, RUCAPS: "Enhancing and implementing knowledge based ICT solutions within high risk and uncertain conditions for agriculture production systems", funded by the European ...[+]
Tipo: Artículo Capítulo de libro

References

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Esteso, A., Alemany, M.M.E., Ortiz, A.: Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models. Int. J. Prod. Res. (2018). https://doi.org/10.1080/00207543.2018.1447706 [+]
Dury, J., Schaller, N., Garcia, F., et al.: Models to support cropping plan and crop rotation decisions. rev. Agron. Sustain. Dev. 32, 567–580 (2012). https://doi.org/10.1007/s13593-011-0037-x

Handayati, Y., Simatupang, T.M., Perdana, T.: Agri-food supply chain coordination: the state-of-the-art and recent developments. Logist. Res. 8(1), 1–15 (2015). https://doi.org/10.1007/s12159-015-0125-4

Esteso, A., Alemany, M.M.E., Ortiz, A.: Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models. Int. J. Prod. Res. (2018). https://doi.org/10.1080/00207543.2018.1447706

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Esteso, A., Alemany, M.M.E., Ortiz, A., Liu, S.: Optimization model to support sustainable crop planning for reducing unfairness among farmers. Cent. Eur. J. Oper. Res. (2021). https://doi.org/10.1007/s10100-021-00751-8

Stadler, H.: A framework for collaborative planning and state-of-the-art. In: Meyr, H., Günther, H.-O. (eds.) Supply Chain Planning, pp. 3–28. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-540-93775-3_1

Ammirato, S., Felicetti, A.M., Ferrara, M., et al.: Collaborative organization models for sustainable development in the agri-food sector. Sustainability 13, 2301 (2021). https://doi.org/10.3390/su13042301

Esteso, A., Alemany, M.M.E., Ortiz, A.: Conceptual framework for managing uncertainty in a collaborative agri-food supply chain context. In: Camarinha-Matos, L.M., Afsarmanesh, H., Fornasiero, R. (eds.) PRO-VE 2017. IAICT, vol. 506, pp. 715–724. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-65151-4_64

Esteso, A., Alemany, M.M.E., Ortiz, Á.: Impact of product perishability on agri-food supply chains design. Appl. Math. Model 96, 20–38 (2021). https://doi.org/10.1016/j.apm.2021.02.027

Alemany, M., Esteso, A., Ortiz, A., del Pino, M.: Centralized and distributed optimization models for the multi-farmer crop planning problem under uncertainty: application to a fresh tomato Argentinean supply chain case study. Comput. Ind. Eng., 107048 (2020). https://doi.org/10.1016/j.cie.2020.107048

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