Title: A RFID-based similarity cluster approach for detecting abnormal logistics paths and its performance evaluation

 

Author: Xiaohua Cao; Qingxia Li

 

Addresses:
School of Logistics Engineering, Wuhan University of Technology, Wuhan, China
School of Logistics Engineering, Wuhan University of Technology, Wuhan, China

 

Journal: Int. J. of Information Technology and Management, 2016 Vol.15, No.4, pp.387 - 400

 

Abstract: Abnormal transportation path can cause the sharp increase of the cost of logistics operation. So it becomes crucial to detect and handle abnormal logistics paths timely in the process of transportation logistics. Based on RFID information acquisition technology, this paper proposes a novel cluster approach to detect abnormal logistics paths. Firstly, it adopts RFID data to describe logistics paths and presents a similarity model of RFID paths according to the sequence feature of RFID nodes in logistics paths. Based on path similarity model, a cluster approach of RFID paths is suggested for detecting abnormal logistics paths. Finally, the performance of the proposed similarity cluster approach is evaluated from the various points of view. The results show that the proposed RFID-based similarity cluster approach can well build high-similarity group of paths and easily find the outliers of clusters. It is well suited to detect abnormal paths in an actual transportation logistics.

 

Keywords: RFID; radio-frequency identification; similarity clusters; abnormal logistics path; ALP; performance evaluation; logistics costs; modelling; path similarity; clustering; transport logistics.

 

DOI: http://dx.doi.org/10.1504/IJITM.2016.10000274

 

Available online 22 Sep 2016

 

 

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