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dc.contributor.author
Bearzotti, Lorena  
dc.contributor.author
Salomone, Hector Enrique  
dc.contributor.author
Chiotti, Omar Juan Alfredo  
dc.date.available
2022-05-24T12:18:37Z  
dc.date.issued
2012-01  
dc.identifier.citation
Bearzotti, Lorena; Salomone, Hector Enrique; Chiotti, Omar Juan Alfredo; An Autonomous Multi-Agent Approach to Supply Chain Event Management; Elsevier Science; International Journal Of Production Economics; 135; 1; 1-2012; 468-478  
dc.identifier.issn
0925-5273  
dc.identifier.uri
http://hdl.handle.net/11336/158125  
dc.description.abstract
Organizations have made significant effort to implement software for planning and scheduling, but disruptive events management is still a problem to be solved. Because of a disruptive event can affect the overall performance of the supply chain, SCEM (Supply Chain Event Management) systems presenting different automation levels such as monitoring, alarm, and decision support have been proposed. However, the management of disruptive events, taking into account the distributed nature of the supply chain, the members´ autonomy, and the ability to exert corrective control actions, has been identified as a problem that requires further research. This work presents an agent-based approach for the SCEM problem, which can perform autonomous corrective control actions to minimize the effect of deviations in the plan that is currently being executed. These control actions consist of a distribution of the variation between supply chain members, using the plan?s slack in a collaborative way. An innovative feature of this approach is its focus on resources, which are affected by disruptive events in a direct way. Based on this approach, a SCEM system is designed as a net of control points defined on resources connected through supply process orders. Two novel aspects are the distributed collaborative inter-organizational architecture of the SCEM system and a Double Contract Net Protocol. This protocol allows a set of resource-representing agents to interact through an agent, representing a supply process order as a mediator. An application to a case study of the Multi-Agent SCEM system implemented with JADE is provided  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Elsevier Science  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
SUPPLY CHAIN  
dc.subject
EVENT MANAGEMENT  
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MULTI-AGENT SYSTEM  
dc.subject
AUTONOMOUS BEHAVIOUR  
dc.subject.classification
Ingeniería de Sistemas y Comunicaciones  
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Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información  
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INGENIERÍAS Y TECNOLOGÍAS  
dc.title
An Autonomous Multi-Agent Approach to Supply Chain Event Management  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2022-05-06T16:20:57Z  
dc.identifier.eissn
1873-7579  
dc.journal.volume
135  
dc.journal.number
1  
dc.journal.pagination
468-478  
dc.journal.pais
Países Bajos  
dc.journal.ciudad
Amsterdam  
dc.description.fil
Fil: Bearzotti, Lorena. Universidad Andrés Bello; Chile  
dc.description.fil
Fil: Salomone, Hector Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina  
dc.description.fil
Fil: Chiotti, Omar Juan Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina  
dc.journal.title
International Journal Of Production Economics  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.ijpe.2011.08.023  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S092552731100377X