TDMA grouping based RFID network planning using hybrid differential evolution algorithm

  • Authors:
  • Xiang Gao;Ying Gao

  • Affiliations:
  • Department of Computer Science and Engineering, Hong Kong University of Science and Technology;School of Computer Science and Educational Software, Guang Zhou University

  • Venue:
  • AICI'10 Proceedings of the 2010 international conference on Artificial intelligence and computational intelligence: Part II
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

With the fast development of Radio Frequency Identification (RFID) technology, RFID network has been applied in different aspects of logistic management. How to effectively deploy the readers becomes a crucial problem in RFID network planning. The planning is related to a complicated optimization problem and interference elimination between readers. To find a good solution in the optimization problem effectively, we introduced Differential Evolution algorithm. To minimize the interference between the readers, we applied TDMA on the network and proposed two methods to group the readers. The first method is a modified version of Differential Evolution algorithm. Since part of the problem domain is binary while the searching space of the Differential Evolution algorithm is in a real domain, we modified the mutation rule of the Differential Evolution algorithm so that it can support binary parameters. The other way is to transform the problem into a graph and apply a maximum cut heuristic on it. The experimental result shows that both methods are effective.