A generalized simulation framework for responsive supply network management

Jin Dong, Wei Wang, Teresa Wu

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Scopus citations

Abstract

Firms are under the pressure to explore various strategies to improve the supply network performance so that customers' demands can be met more responsively. Many of the challenges fromimplementing the strategies lie in the distributed and dynamic nature of the network where geographically dispersed entities may have different goals and objectives. Additionally, irregularities and disruptions occurring at any point in the network may propagate through the network and amplify the negative impact. These disruptions, often occurring without warning due to the dynamic nature of a supply network, can lead to poor performance of the supply network. A key component in responsive supply network management is to proactively assess the robustness and resilience to disruption of a supply network.Discrete Event Simulation (DES) can achieve this. In this chapter, we introduce a simulation tool developed by IBM China Research Lab, named General Business Simulation Environment (GBSE). It can capture supply network dynamics with a fine level of granularity and provide useful insights to supply network's real operations. GBSE is designed for tactical-level decision making, and may be useful for supply network what-if analysis and risk analysis. The architecture of GBSE is detailed in this chapter followed by several scenarios in an automobile supply network to demonstrate the applicability of GBSE to assess the responsiveness of a supply network.

Original languageEnglish (US)
Title of host publicationManaging Supply Chain Risk and Vulnerability
Subtitle of host publicationTools and Methods for Supply Chain Decision Makers
PublisherSpringer London
Pages67-88
Number of pages22
ISBN (Print)9781848826335
DOIs
StatePublished - 2009

ASJC Scopus subject areas

  • Engineering(all)

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    Dong, J., Wang, W., & Wu, T. (2009). A generalized simulation framework for responsive supply network management. In Managing Supply Chain Risk and Vulnerability: Tools and Methods for Supply Chain Decision Makers (pp. 67-88). Springer London. https://doi.org/10.1007/978-1-84882-634-2_5