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Supply chain simulation tools and techniques: a survey
Open accessAbstract
The main contribution of this paper is twofold: it surveys different types of simulation for supply chain management; it discusses several methodological issues. These different types of simulation are spreadsheet simulation, system dynamics, discrete-event simulation and business games. Which simulation type should be applied, depends on the type of managerial question to be answered by the model. The methodological issues concern validation and verification, sensitivity, optimisation, and robustness analyses. This sensitivity analysis yields a shortlist of the truly important factors in large simulation models with (say) a hundred factors. The robustness analysis optimises the important factors controllable by management, while accounting for the noise created by the important non-controllable, environmental factors. The various methodological issues are illustrated by a case study involving the simulation of a supply chain in the mobile communications industry in Sweden. In general, simulation is important because it may support the quantification of the benefits resulting from supply chain management.
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Compensation of input delay that depends on delayed input
Diagne, M., Bekiaris-Liberis, N., & Krstic, M. (2017) · Automatica · doi:10.1016/j.automatica.2017.07.069 · Cited by 36
Metadata
- Authors
- Kleijnen, J. P. C.
- Venue
- International Journal of Simulation and Process Modelling
- Publisher
- Inderscience Publishers
- Published
- 2005
- Volume
- 1
- Issue
- 1/2
- Pages
- 82
- ISSN
- 1740-2123 (ISSN-L)
- 1740-2131
- OpenAlex
- W2143402903
- Cited by
- 253
- References
- 0
- FWCI
- 23.02
- Type
- journal article
- Language
- en
- Open access
- green
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- Kleijnen, J. P. C. (2005). Supply chain simulation tools and techniques: a survey. International Journal of Simulation and Process Modelling. https://doi.org/10.1504/ijspm.2005.007116
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.