Decision-making computationally aided in the management of energy sources used in agrifood industries

Detalhes bibliográficos
Autor(a) principal: Zocca, Renan Oliveira
Data de Publicação: 2019
Outros Autores: Gaspar, Pedro Dinis, Silva, Pedro Dinho da, Santos, Fernando Charrua, Andrade, Luís P., Nunes, José
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.6/7289
Resumo: In an increasingly competitive society with an unfavourable economic environment, it is necessary for Small and Medium Enterprises (SMEs) to update themselves, thereby increasing their efficiency. Companies increasingly use computational tools to support the development of predictive scenarios in order to facilitate decision-making. However, the tools developed for SMEs are not always expedite and simple to use. The tool presented in this article intends to support the management of energy sources used by agro-industrial companies. It aims to facilitate and promote the implementation of a new culture of business management, in this sector so important at national level. The computational part is directed to support the decision-making on the selection of fossil or renewable energy sources to be used in a particular agroindustry, by presenting the average values of the energy consumption, cost and emissions associated with each selected energy source.
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spelling Decision-making computationally aided in the management of energy sources used in agrifood industriesEnergy consumptionEnergy managementComputational toolDecision makingIn an increasingly competitive society with an unfavourable economic environment, it is necessary for Small and Medium Enterprises (SMEs) to update themselves, thereby increasing their efficiency. Companies increasingly use computational tools to support the development of predictive scenarios in order to facilitate decision-making. However, the tools developed for SMEs are not always expedite and simple to use. The tool presented in this article intends to support the management of energy sources used by agro-industrial companies. It aims to facilitate and promote the implementation of a new culture of business management, in this sector so important at national level. The computational part is directed to support the decision-making on the selection of fossil or renewable energy sources to be used in a particular agroindustry, by presenting the average values of the energy consumption, cost and emissions associated with each selected energy source.ElsevieruBibliorumZocca, Renan OliveiraGaspar, Pedro DinisSilva, Pedro Dinho daSantos, Fernando CharruaAndrade, Luís P.Nunes, José2019-10-18T14:01:25Z20192019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.6/7289eng1876-610210.1016/j.egypro.2019.02.063metadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-06T02:30:27Zoai:ubibliorum.ubi.pt:10400.6/7289Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:47:50.327222Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Decision-making computationally aided in the management of energy sources used in agrifood industries
title Decision-making computationally aided in the management of energy sources used in agrifood industries
spellingShingle Decision-making computationally aided in the management of energy sources used in agrifood industries
Zocca, Renan Oliveira
Energy consumption
Energy management
Computational tool
Decision making
title_short Decision-making computationally aided in the management of energy sources used in agrifood industries
title_full Decision-making computationally aided in the management of energy sources used in agrifood industries
title_fullStr Decision-making computationally aided in the management of energy sources used in agrifood industries
title_full_unstemmed Decision-making computationally aided in the management of energy sources used in agrifood industries
title_sort Decision-making computationally aided in the management of energy sources used in agrifood industries
author Zocca, Renan Oliveira
author_facet Zocca, Renan Oliveira
Gaspar, Pedro Dinis
Silva, Pedro Dinho da
Santos, Fernando Charrua
Andrade, Luís P.
Nunes, José
author_role author
author2 Gaspar, Pedro Dinis
Silva, Pedro Dinho da
Santos, Fernando Charrua
Andrade, Luís P.
Nunes, José
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv uBibliorum
dc.contributor.author.fl_str_mv Zocca, Renan Oliveira
Gaspar, Pedro Dinis
Silva, Pedro Dinho da
Santos, Fernando Charrua
Andrade, Luís P.
Nunes, José
dc.subject.por.fl_str_mv Energy consumption
Energy management
Computational tool
Decision making
topic Energy consumption
Energy management
Computational tool
Decision making
description In an increasingly competitive society with an unfavourable economic environment, it is necessary for Small and Medium Enterprises (SMEs) to update themselves, thereby increasing their efficiency. Companies increasingly use computational tools to support the development of predictive scenarios in order to facilitate decision-making. However, the tools developed for SMEs are not always expedite and simple to use. The tool presented in this article intends to support the management of energy sources used by agro-industrial companies. It aims to facilitate and promote the implementation of a new culture of business management, in this sector so important at national level. The computational part is directed to support the decision-making on the selection of fossil or renewable energy sources to be used in a particular agroindustry, by presenting the average values of the energy consumption, cost and emissions associated with each selected energy source.
publishDate 2019
dc.date.none.fl_str_mv 2019-10-18T14:01:25Z
2019
2019-01-01T00:00:00Z
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1876-6102
10.1016/j.egypro.2019.02.063
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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