Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 35, Issue 3, Pages 1166-1176Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2007.08.015
Keywords
RFID-enabled non-deterministic supply chain; forward-backward analysis; fuzzy cognitive map (FCM); weight learning; genetic algorithm
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Funding
- National Research Foundation of Korea [R01-2006-000-10014-0] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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Supply chain is a non-deterministic system in which uncontrollable external states with probabilistic behaviors (e.g., machine failure rate) influence on internal states (e.g., inventory level) significantly through complex causal relationships. Thanks to Radio frequency identification (RFID) technology, real time monitoring of the states is now possible. The current research on processing RFID data is, however, limited to statistical information. The goal of this research is to mine bidirectional cause-effect knowledge from the state data. In detail, fuzzy cognitive map (FCM) model of supply chain is developed. By using genetic algorithm, the weight matrix of the FCM model is discovered with the past state data, and forward (what-if) analysis is performed. Also, when sudden change in a certain state is detected, its cause is sought from the past state data throughout backward analysis. Simulation based experiments are provided to show the performance of the proposed forward-backward analysis methodology. (C) 2007 Elsevier Ltd. All rights reserved.
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