利用增强烟花算法对RFID网络进行规划

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。

Enhanced fireworks algorithm for RFID network planning

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.