Deterministic and Uncertain Methods and Models for Managing Agri-Food Supply Chain
[EN] The market for agricultural products has grown substantially. At the same time, social concern in food issues such as food safety, food quality, traceability and sustainability is constantly increasing. These reasons have pointed out the need of new models and tools to manage the agri-food supp...
| Autores: | , , |
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| Tipo de documento: | artigo |
| Data de publicação: | 2017 |
| País: | España |
| Recursos: | Universitat Politècnica de València (UPV) |
| Repositório: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglês |
| OAI Identifier: | oai:riunet.upv.es:10251/108673 |
| Acesso em linha: | https://riunet.upv.es/handle/10251/108673 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Agri-food Supply chain Mathematical programming Deterministic Uncertainty ORGANIZACION DE EMPRESAS |
| Resumo: | [EN] The market for agricultural products has grown substantially. At the same time, social concern in food issues such as food safety, food quality, traceability and sustainability is constantly increasing. These reasons have pointed out the need of new models and tools to manage the agri-food supply chains while considering the characteristics that differentiate them from other industrial supply chains as well as the uncertainties present in the sector. Thus, the aim of this paper is to present the current status of a project which mains objectives are to describe the complexity faced by agri-food supply chain decision makers, and to develop new tools based on mathematical programming models to help the decision making process in agri-food supply chain planning. These models novelty will include the consideration of the inherent characteristics of agri-food supply chains and the sources of uncertainty present in the sector. The proposed models and tools will be applied to a real agri-food supply chain in order to prove their validity and applicability and to compare the results obtained by deterministic and uncertain tools. |
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