RFID network planning using a multi-swarm optimizer

  • Authors:

  • Hanning Chen;Yunlong Zhu;Kunyuan Hu;Tao Ku

  • Affiliations:

  • Key Laboratory of Industrial Informatics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China;Key Laboratory of Industrial Informatics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China;Key Laboratory of Industrial Informatics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China;Key Laboratory of Industrial Informatics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China

  • Venue:
  • Journal of Network and Computer Applications
  • Year:
  • 2011

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Abstract

In this paper, we develop an optimization model for planning the positions of readers in the RFID network based on a novel multi-swarm particle swarm optimizer called PS^2O. The main idea of PS^2O is to extend the single population PSO to the interacting multi-swarms model by constructing hierarchical interaction topology and enhanced dynamical update equations. This algorithm, which is conceptually simple and easy to implement, has considerable potential for solving complex optimization problems. With five mathematical benchmark functions, PS^2O is proved to have significantly better performance than five successful variants of PSO. PS^2O is then used for solving the real-world RFID network planning problem. Simulation results show that the proposed algorithm proves to be superior for planning RFID networks than canonical PSO, multi-swarm cooperative PSO (MCPSO), and two evolutionary algorithms, namely genetic algorithm with elitism (EGA) and self-adaptive evolution strategies (SA-ES), in terms of optimization accuracy and computation robustness.