Managing uncertain inventory in supply chain with neural network and radio frequency identification (RFID)

Ka Man Lee, Ng Wenwei Benjamin, Shaligram Pokharel

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review

1 Citation (Scopus)


Demand uncertainty leads to fluctuations in inventory position at each echelon of a supply chain causing bullwhip effect, which can lead to significant cost and loss of efficiency and waste of resources. One of the aspects that can reduce potential bullwhip effect is the sharing of real time information for which the recently mass produced Radio Frequency Identification (RFID) can be of great value. The use of RFID technology can also help in increasing the visibility of the flow of goods and material, keeping track of the location and quantity at each distribution centre and warehouses. This will also help in the periodic and near real time optimization of inventory level of goods and material. The data collected with RFID can be analysed in artificial Neural Network (NN) to forecast the future demand. In this chapter, a framework is proposed by combining RFID with artificial neural network so that lean logistics can be realized in the supply chain.
Original languageEnglish
Title of host publicationSupply Chain Innovation for Competing in Highly Dynamic Markets
Subtitle of host publicationChallenges and Solutions
PublisherIGI Global
Number of pages16
ISBN (Print)9781609605858
Publication statusPublished - 1 Dec 2011
Externally publishedYes

ASJC Scopus subject areas

  • Business, Management and Accounting(all)

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