Abstract
This paper presents a heterogeneous (cognitive/reactive) agent based approach to model supply chains. The proposed model based on an actors’ representation introduce the behavioural studies of active entities constituting the logistics organization. Supply chains member’s behaviours are split up into two categories: deliberative and operational. The design and exploitation of distributed simulation model with multi-agents systems permits to support the representation of entities realizing decision-making and operational activities. To facilitate the design of such models, a dedicated agent model is proposed for each category of behaviour: the Decision Agent and Simulation Agent.
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References
Amblard, F., Ferrand, N.: Modélisation multi agents de l’évolution de réseaux sociaux. Modéles et SMA pour la gestion de l’environnement et des territoires, 153-168 (1998)
Booch, G., Rumbaugh, J., Jacobson, I.: The Unified Modeling Language User Guide. Addison-Wesley, Reading (1999)
Ferrarini, A., Labarthe, O., Espinasse, B.: Modelling and Simulation of Supply Chains with a Multi Agent System. 13th European Simulation Symposium, France (2001)
Fisher, K., Müller, J.P., Pischel, M.: Cooperative transportation schedulling: an application domain for DAI. Applied Artificial Intelligence 10, 1–33 (1996)
Huget, M.P.: An Application of Agent UML to Supply Chain Management. In: Proceedings of Agent Oriented Information System (AOIS 2002), Italy (2002)
Meurisse, T., Vanbergue, D.: Et maintenant á qui le tour? Apercu de la problématique de conception de simulations multi agents. Laboratoire d’Informatique de Paris 6 (2001)
Moulin, B., Chaib-Draa, B.: An Overview of Distributed Artificial Intelligence. Foundations of Distributed Artificial Intelligence, O’Hare and .Jennings, 3–55 (1996)
Odell, J., Parunak, H., Bauer, B.: Representing agent interaction protocols in UML. In: AAAI Agents conference, Spain (2000)
Parunak, H.: What can Agents do in Industry, and Why? An Overview of Industrially Oriented R&D at CEC. Industrial Technology Institute (1998)
Parunak, H., Savit, R., Riolo, R.L.: Agent-Based Modeling vs. Equation-Based Modeling: A case Study and User’s Guide. Center for Electronic Commerce (1998)
Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice-Hall, Englewood Cliffs (1995)
Sadeh, N., Hildum, D., Kjenstad, D., Tseng, A.: MASCOT: An Agent-based Architecture for Dynamic Supply Chain and Coordination in the Internet Economy. Production Planning & Control 12(3) (2001)
Teigen, R.: Information Flow in a Supply Chain Management System, Ph. D. Thesis, University of Toronto (1997)
Tranvouez, E., Espinasse, B.: Protocoles de coopération pour le réordonancement d’atelier. Journées Francophone sur l’intelligence Artificielle distribuée et SMA (1999)
Wooldridge, M., Jennings, N.R.: Agents Theories, Architectures, and languages: A Survey. Notes in Artificial Intelligence, Wooldridge and Jennings, 1-39 (1994)
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Labarthe, O., Tranvouez, E., Ferrarini, A., Espinasse, B., Montreuil, B. (2003). A Heterogeneous Multi-agent Modelling for Distributed Simulation of Supply Chains. In: Mařík, V., McFarlane, D., Valckenaers, P. (eds) Holonic and Multi-Agent Systems for Manufacturing. HoloMAS 2003. Lecture Notes in Computer Science(), vol 2744. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45185-3_13
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DOI: https://doi.org/10.1007/978-3-540-45185-3_13
Publisher Name: Springer, Berlin, Heidelberg
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