Title

Detecting And Analysing Patterns In Supply Chain Behaviour

Keywords

eigen value analysis; neural networks; NNs; SCM; SD; supply chain management; supply chain modelling; system dynamics

Abstract

Using outputs of a supply chain system dynamics model, neural networks’ pattern recognition capabilities and eigen value analysis are utilised to detect and analyse behavioural changes in the supply chain and predict their impact in the short- and long-term horizons on performances. Neural networks are used to detect changes in the supply chain behaviour at a very early stage of their occurrence so that an enterprise would have enough time to respond and counteract any unwanted situations. Then, the principles of stability and controllability are used to apply and make modifications to the information and material flows to avoid undesirable behaviours. © 2006 Inderscience Enterprises Ltd.

Publication Date

1-1-2006

Publication Title

International Journal of Simulation and Process Modelling

Volume

2

Issue

3-4

Number of Pages

198-209

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1504/ijspm.2006.012647

Socpus ID

84946208986 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84946208986

This document is currently not available here.

Share

COinS