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
CIC Digital (CICBA)
Institución
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
OAI Identificador
oai:digital.cic.gba.gob.ar:11746/10594

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network_name_str CIC Digital (CICBA)
spelling 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
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info:eu-repo/semantics/acceptedVersion
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dc.identifier.none.fl_str_mv https://digital.cic.gba.gob.ar/handle/11746/10594
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reponame_str CIC Digital (CICBA)
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instname_str Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron_str CICBA
institution CICBA
repository.name.fl_str_mv CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
repository.mail.fl_str_mv marisa.degiusti@sedici.unlp.edu.ar
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