A Heuristic Approach for Allocation of Data To Rfid Tags: A Data Allocation Knapsack Problem (dakp)
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Date
2012
Authors
Davis, Lauren
Samanlıoğlu, Funda
Jiang, Xiaochun
Mota, Daniel
Stanfield, Paul
Journal Title
Journal ISSN
Volume Title
Publisher
Pergamon-Elsevier Science Ltd
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Abstract
Durable products and their components are increasingly being equipped with one of several forms of automatic identification technology such as radio frequency identification (RFID). This technology enables data collection, storage, and transmission of product information throughout its life cycle. Ideally all available relevant information could be stored on RFID tags with new information being added to the tags as it becomes available. However, because of the finite memory capacity of RFID tags along with the magnitude of potential lifecycle data, users need to be more selective in data allocation. In this research, the data allocation problem is modeled as a variant of the nonlinear knapsack problem. The objective is to determine the number of items to place on the tag such that the value of the "unexplained" data left off the tag is minimized. A binary encoded genetic algorithm is proposed and an extensive computational study is performed to illustrate the effectiveness of this approach. Additionally, we discuss some properties of the optimal solution which can be effective in solving more difficult problem instances. (C) 2011 Elsevier Ltd. All rights reserved.
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Keywords
RFID tags, Data allocation, Knapsack problem
Turkish CoHE Thesis Center URL
Fields of Science
Citation
8
WoS Q
Q2
Scopus Q
Q1
Source
Volume
39
Issue
1
Start Page
93
End Page
104