Collaborative, Distributed Simulations of Agri-Food Supply Chains: Analysis on How Linking Theory and Practice by Using Multi-agent Structures
- Autores
- Fernández, Alejandro; Hernandez Hormazabal, Jorge E.; Liu, Shaofeng; Panetto, Hervé; Pankow, Matías Nahuel; Sanchez, Esteban
- Año de publicación
- 2019
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión aceptada
- Descripción
- Simulations help to understand and predict the behaviour of complex phenomena?s, likewise distributed socio-technical systems or how stakeholders interacts in complex domains. Such domains are normally based on networked based interaction, where information, product and decision flows comes in to play, especially under the well-known supply chains structures. Although tools exist to simulate supply chains, they do not adequately support multiple stakeholders to collaboratively create and explore a variety of decision-making scenarios. Hence, in order to provide a preliminary understanding on how these interaction affects stakeholders decision-making, this research presents an study, analysis and proposal development of robust platform to collaboratively build and simulate communication among supply chain. Since realistic supply chain behaviours are complex, a multi-agent approach was selected in order to represent such complexities in a standardised manner. The platform provides agent behaviours for common agent patterns. It provides extension hotspots to implement more specific agent behaviour for expert users (that requires programming). Therefore, as key contribution, technical aspects of the platform are presented, and also the role of multi-level supply chain scenario simulation is discussed and analysed, especially under de context of digital supply chain transformation in the agri-food context. Finally, we discuss lessons learned from early tests with the reference implementation of the platform.
- Materia
-
Ciencias de la Computación
Digital transformation
Simulations
Supply chain - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-nd/4.0/
- Repositorio
- Institución
- Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
- OAI Identificador
- oai:digital.cic.gba.gob.ar:11746/10594
Ver los metadatos del registro completo
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Collaborative, Distributed Simulations of Agri-Food Supply Chains: Analysis on How Linking Theory and Practice by Using Multi-agent StructuresFernández, AlejandroHernandez Hormazabal, Jorge E.Liu, ShaofengPanetto, HervéPankow, Matías NahuelSanchez, EstebanCiencias de la ComputaciónDigital transformationSimulationsSupply chainSimulations help to understand and predict the behaviour of complex phenomena?s, likewise distributed socio-technical systems or how stakeholders interacts in complex domains. Such domains are normally based on networked based interaction, where information, product and decision flows comes in to play, especially under the well-known supply chains structures. Although tools exist to simulate supply chains, they do not adequately support multiple stakeholders to collaboratively create and explore a variety of decision-making scenarios. Hence, in order to provide a preliminary understanding on how these interaction affects stakeholders decision-making, this research presents an study, analysis and proposal development of robust platform to collaboratively build and simulate communication among supply chain. Since realistic supply chain behaviours are complex, a multi-agent approach was selected in order to represent such complexities in a standardised manner. The platform provides agent behaviours for common agent patterns. It provides extension hotspots to implement more specific agent behaviour for expert users (that requires programming). Therefore, as key contribution, technical aspects of the platform are presented, and also the role of multi-level supply chain scenario simulation is discussed and analysed, especially under de context of digital supply chain transformation in the agri-food context. Finally, we discuss lessons learned from early tests with the reference implementation of the platform.2019-08-15info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/10594enginfo:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-030-28464-0_42info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-29T13:39:58Zoai:digital.cic.gba.gob.ar:11746/10594Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-29 13:39:59.077CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse |
dc.title.none.fl_str_mv |
Collaborative, Distributed Simulations of Agri-Food Supply Chains: Analysis on How Linking Theory and Practice by Using Multi-agent Structures |
title |
Collaborative, Distributed Simulations of Agri-Food Supply Chains: Analysis on How Linking Theory and Practice by Using Multi-agent Structures |
spellingShingle |
Collaborative, Distributed Simulations of Agri-Food Supply Chains: Analysis on How Linking Theory and Practice by Using Multi-agent Structures Fernández, Alejandro Ciencias de la Computación Digital transformation Simulations Supply chain |
title_short |
Collaborative, Distributed Simulations of Agri-Food Supply Chains: Analysis on How Linking Theory and Practice by Using Multi-agent Structures |
title_full |
Collaborative, Distributed Simulations of Agri-Food Supply Chains: Analysis on How Linking Theory and Practice by Using Multi-agent Structures |
title_fullStr |
Collaborative, Distributed Simulations of Agri-Food Supply Chains: Analysis on How Linking Theory and Practice by Using Multi-agent Structures |
title_full_unstemmed |
Collaborative, Distributed Simulations of Agri-Food Supply Chains: Analysis on How Linking Theory and Practice by Using Multi-agent Structures |
title_sort |
Collaborative, Distributed Simulations of Agri-Food Supply Chains: Analysis on How Linking Theory and Practice by Using Multi-agent Structures |
dc.creator.none.fl_str_mv |
Fernández, Alejandro Hernandez Hormazabal, Jorge E. Liu, Shaofeng Panetto, Hervé Pankow, Matías Nahuel Sanchez, Esteban |
author |
Fernández, Alejandro |
author_facet |
Fernández, Alejandro Hernandez Hormazabal, Jorge E. Liu, Shaofeng Panetto, Hervé Pankow, Matías Nahuel Sanchez, Esteban |
author_role |
author |
author2 |
Hernandez Hormazabal, Jorge E. Liu, Shaofeng Panetto, Hervé Pankow, Matías Nahuel Sanchez, Esteban |
author2_role |
author author author author author |
dc.subject.none.fl_str_mv |
Ciencias de la Computación Digital transformation Simulations Supply chain |
topic |
Ciencias de la Computación Digital transformation Simulations Supply chain |
dc.description.none.fl_txt_mv |
Simulations help to understand and predict the behaviour of complex phenomena?s, likewise distributed socio-technical systems or how stakeholders interacts in complex domains. Such domains are normally based on networked based interaction, where information, product and decision flows comes in to play, especially under the well-known supply chains structures. Although tools exist to simulate supply chains, they do not adequately support multiple stakeholders to collaboratively create and explore a variety of decision-making scenarios. Hence, in order to provide a preliminary understanding on how these interaction affects stakeholders decision-making, this research presents an study, analysis and proposal development of robust platform to collaboratively build and simulate communication among supply chain. Since realistic supply chain behaviours are complex, a multi-agent approach was selected in order to represent such complexities in a standardised manner. The platform provides agent behaviours for common agent patterns. It provides extension hotspots to implement more specific agent behaviour for expert users (that requires programming). Therefore, as key contribution, technical aspects of the platform are presented, and also the role of multi-level supply chain scenario simulation is discussed and analysed, especially under de context of digital supply chain transformation in the agri-food context. Finally, we discuss lessons learned from early tests with the reference implementation of the platform. |
description |
Simulations help to understand and predict the behaviour of complex phenomena?s, likewise distributed socio-technical systems or how stakeholders interacts in complex domains. Such domains are normally based on networked based interaction, where information, product and decision flows comes in to play, especially under the well-known supply chains structures. Although tools exist to simulate supply chains, they do not adequately support multiple stakeholders to collaboratively create and explore a variety of decision-making scenarios. Hence, in order to provide a preliminary understanding on how these interaction affects stakeholders decision-making, this research presents an study, analysis and proposal development of robust platform to collaboratively build and simulate communication among supply chain. Since realistic supply chain behaviours are complex, a multi-agent approach was selected in order to represent such complexities in a standardised manner. The platform provides agent behaviours for common agent patterns. It provides extension hotspots to implement more specific agent behaviour for expert users (that requires programming). Therefore, as key contribution, technical aspects of the platform are presented, and also the role of multi-level supply chain scenario simulation is discussed and analysed, especially under de context of digital supply chain transformation in the agri-food context. Finally, we discuss lessons learned from early tests with the reference implementation of the platform. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-08-15 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/acceptedVersion http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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conferenceObject |
status_str |
acceptedVersion |
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https://digital.cic.gba.gob.ar/handle/11746/10594 |
url |
https://digital.cic.gba.gob.ar/handle/11746/10594 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-030-28464-0_42 |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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openAccess |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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