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A heuristic approach for allocation of data to RFID tags: A data allocation knapsack problem
Computers and Operations Research (2012)
  • Lauren B Davis
  • Funda Samanlioglu, Kadir Has University
  • Xiaochun Jiang
  • Daniel Mota
  • Paul Stanfield
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.
  • RFID tags; Dataallocation; Knapsackproblem
Publication Date
Citation Information
Lauren B Davis, Funda Samanlioglu, Xiaochun Jiang, Daniel Mota, et al.. "A heuristic approach for allocation of data to RFID tags: A data allocation knapsack problem" Computers and Operations Research Vol. 39 Iss. 1 (2012)
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