MODELLING COLLABORATIVE FORECASTING IN DECENTRALIZED SUPPLY CHAIN NETWORKS WITH A MULTIAGENT SYSTEM

Jorge E. Hernández, Raúl Poler, Josefa Mula

Abstract

Information technology has become a strong modelling approach to support the complexities involved in a process. One example of this technology is the multiagent system which, from a decentralized supply chain configuration perspective, supports the information sharing processes that any of its node will be able to carry out to support its process in a collaborative manner, for example, the forecasting process. Therefore, this paper presents a novel collaborative forecasting model in supply chain networks by considering a multiagent system modelling approach. The hypothesis presented herein is that by collaborating in the information exchange process, less errors are made in the forecasting process.

References

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Paper Citation


in Harvard Style

E. Hernández J., Poler R. and Mula J. (2009). MODELLING COLLABORATIVE FORECASTING IN DECENTRALIZED SUPPLY CHAIN NETWORKS WITH A MULTIAGENT SYSTEM . In Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8111-85-2, pages 372-375. DOI: 10.5220/0002008503720375


in Bibtex Style

@conference{iceis09,
author={Jorge E. Hernández and Raúl Poler and Josefa Mula},
title={MODELLING COLLABORATIVE FORECASTING IN DECENTRALIZED SUPPLY CHAIN NETWORKS WITH A MULTIAGENT SYSTEM},
booktitle={Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2009},
pages={372-375},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002008503720375},
isbn={978-989-8111-85-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - MODELLING COLLABORATIVE FORECASTING IN DECENTRALIZED SUPPLY CHAIN NETWORKS WITH A MULTIAGENT SYSTEM
SN - 978-989-8111-85-2
AU - E. Hernández J.
AU - Poler R.
AU - Mula J.
PY - 2009
SP - 372
EP - 375
DO - 10.5220/0002008503720375