We consider a problem of quantifying risk factors and identifying most informative (or vulnerable) components of the supply chain in terms of the amount of information about the risks and corresponding losses. This knowledge is beneficial for the selection of risk-prevention decisions. Shannons entropy is shown to be a powerful tool for risk management in hierarchical supply chains. An efficient algorithm is proposed that permits to reduce the size of the supply chain model without a loss of essential information about the risks and their economic consequences. A case study is presented to demonstrate the validity of the entropy-based approach.
|Number of pages||15|
|Journal||International Journal of Production Research|
|State||Published - 17 Nov 2015|
Bibliographical notePublisher Copyright:
© 2014 Taylor and Francis.
- Supply chain management
- information entropy
- information value