计算机工程与应用 ›› 2017, Vol. 53 ›› Issue (3): 23-27.DOI: 10.3778/j.issn.1002-8331.1607-0055

• 热点与综述 • 上一篇    下一篇

利用增强烟花算法对RFID网络进行规划

杨志升,朱参世,高杨军   

  1. 空军工程大学 装备管理与安全工程学院,西安 710051
  • 出版日期:2017-02-01 发布日期:2017-05-11

Enhanced fireworks algorithm for RFID network planning

YANG Zhisheng, ZHU Canshi, GAO Yangjun   

  1. College of Material Management and Safety Engineering, Air Force Engineering University, Xi’an 710051, China
  • Online:2017-02-01 Published:2017-05-11

摘要: 为了实现面向复杂环境下的RFID(Radio Frequency Identification)网络规划,提出利用增强烟花算法,并采用分层方法来实现多目标RFID网络的规划。通过建立优化模型,在满足标签100%覆盖率、部署更少的阅读器、使用较少的发射功率和避免信号干扰四个目标的基础上,使用标准基测试集进行测试,与GPSO(Global topology Particle Swarm Optimization)、VNPSO(Von Neumann topology Particle Swarm Optimization)、GPSO-RNP(Global topology Particle Swarm Optimization-RFID Network Planning)和VNPSO-RNP(Von Neumann topology Particle Swarm Optimization-RFID Network Planning)四种算法进行了对比分析。实验结果表明,增强烟花算法在对多目标RFID进行网络规划时表现更优异,可以更有效地求出最优化方案。

关键词: 增强烟花算法, 无线射频识别, 网络规划, 优化

Abstract: In order to realize the RFID(Radio Frequency Identification)network planning for thecomplex environment, in the implementation of the enhanced fireworks algorithm for multi-objective RFID network planning problem,this paper uses hierarchical approach to objectives. It proposes an optimization model of RFID network system that is, to achieve tag 100% coverage, to deploy fewer readers, to avoid signal interference while using less transmitting power. For experimental purposes it uses standard benchmark sets and makes a comparative analysis withGPSO(Global topology Particle Swarm Optimization)、VNPSO(Von Neumann topology Particle Swarm Optimization)、GPSO-RNP(Global topology Particle Swarm Optimization-RFID Network Planning)and VNPSO-RNP(Von Neumann topology Particle Swarm Optimization-RFID Network Planning). Experiment results show that the algorithm can be more effective in theplanning of multi-objectiveRFIDnetwork, and the optimization scheme can be obtained more effectively.