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Using simulation for supply chain analysis: reviewing and proposing distributed simulation frameworks

Simulation modelling and analysis can be an extremely effective tool for supply chain performance analysis. Many development proposals apply distributed simulation to this context. The aim of this paper is to present an overview of such standards, models and/or architectures, describing the technolo...

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Bibliographic Details
Published in:Production planning & control 2006-03, Vol.17 (2), p.167-175
Main Authors: Bandinelli, R., Rapaccini, M., Tucci, M., Visintin, F.
Format: Article
Language:English
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Summary:Simulation modelling and analysis can be an extremely effective tool for supply chain performance analysis. Many development proposals apply distributed simulation to this context. The aim of this paper is to present an overview of such standards, models and/or architectures, describing the technological choices related to each of them, and to propose how and when a distributed supply chain simulation framework is to be used. Our proposal includes brief examples and experiences from experimental researches. Though detailed implementation of the framework is not in the scope of this paper, references for further information are given. In order to provide a coherent presentation of the proposal, this paper will be organised as follows: Section 1 introduces the context of supply chain management. Section 2 shows how distributed supply chain simulation (DSCS) can be an extremely effective tool for performance analysis in supply chain planning and optimisation. Section 3 points out the available technologies and the technological aspects of a distributed simulation framework, such as inter-process communication (IPC) standards and real-time infrastructures. Section 4 describes how the DSCS framework can be utilised. Section 5 reports on framework validation and gives an outlook on the experimental researches. Finally, section 6 concludes the paper summarising the proposal and discussing its benefits and drawbacks.
ISSN:0953-7287
1366-5871
DOI:10.1080/09537280500224051