Title: Detecting and analysing patterns in Supply Chain behaviour

Authors: Luis Rabelo, Magdy Helal, Jeffrey W. Dawson, Reinaldo J. Moraga

Addresses: Industrial Engineering and Management Systems Department, University of Central Florida, Orlando, FL 32816, USA. ' Industrial Engineering and Management Systems Department, University of Central Florida, Orlando, FL 32816, USA. ' Industrial Engineering and Management Systems Department, University of Central Florida, Orlando, FL 32816, USA. ' Department of Industrial and Systems Engineering, Northern Illinois University, DeKalb, IL 60115-2854, USA

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.

Keywords: supply chain modelling; supply chain management; SCM; system dynamics; neural networks; ANNs; eigenvalue analysis; supply chain behaviour; information flow; material flow.

DOI: 10.1504/IJSPM.2006.012647

International Journal of Simulation and Process Modelling, 2006 Vol.2 No.3/4, pp.198 - 209

Published online: 05 Mar 2007 *

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