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Workload Assignment in Production Networks by Multi Agent Architecture

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Foundations of Computational, Intelligence Volume 1

Part of the book series: Studies in Computational Intelligence ((SCI,volume 201))

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Abstract

Distributed production networks are considered organizational structures able to match agility and efficiency necessary to compete in the global market. Performances of such organization structures heavily depend on the ability of the network actors of coordinating their activities. This chapter concerns the low level of the production planning that is aim is to allocation the orders to the distributed plant. The orders assigned by the medium level have to be allocated to the plant able to manufacture the product. A this level the coordination among the plant is crucial activity to purse an high level of performance. In this context, three approaches for coordinating production planning activities within production networks are proposed. Moreover, the proposed approaches are modeled and designed by a Multi Agent Technology and a negotiation model is proposed. In order to test the functionality of the proposed agent based distributed architecture for distributed production planning, a proper simulation environment has been developed. Moreover, a benchmark model is proposed in order to evaluate the performances of the proposed approaches. The Multi Agent System and simulation environment can be utilized to learn the optimal coordination policy to adopt in distributed production planning problem.

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Renna, P., Argoneto, P. (2009). Workload Assignment in Production Networks by Multi Agent Architecture. In: Hassanien, AE., Abraham, A., Vasilakos, A.V., Pedrycz, W. (eds) Foundations of Computational, Intelligence Volume 1. Studies in Computational Intelligence, vol 201. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01082-8_10

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  • DOI: https://doi.org/10.1007/978-3-642-01082-8_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01081-1

  • Online ISBN: 978-3-642-01082-8

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