Forward-backward analysis of RFID-enabled supply chain using fuzzy cognitive map and genetic algorithm

Moon Chan Kim, Chang Ouk Kim, Seong Rok Hong, Ick Hyun Kwon

Research output: Contribution to journalArticlepeer-review

60 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)1166-1176
Number of pages11
JournalExpert Systems with Applications
Issue number3
Publication statusPublished - 2008 Oct

Bibliographical note

Funding Information:
This work was supported by Grant No. R01-2006-000-10014-0 from the Basic Research Program of the Korea Science & Engineering Foundation.

All Science Journal Classification (ASJC) codes

  • General Engineering
  • Computer Science Applications
  • Artificial Intelligence


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