利用增强烟花算法对RFID网络进行规划  

Enhanced fireworks algorithm for RFID network planning

作　　者：杨志升[1] 朱参世[1] 高杨军[1] YANG Zhisheng;ZHU Canshi;GAO Yangjun(College of Material Management and Safety Engineering, Air Force Engineering University, Xi’an 710051, China)

机构地区：[1]空军工程大学装备管理与安全工程学院,西安710051

出　　处：《计算机工程与应用》2017年第3期23-27,共5页Computer Engineering and Applications

基　　金：国家自然科学基金青年基金项目(No.71601183)

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。In order to realize the RFID(Radio Frequency Identification)network planning for thecomplex environment,inthe implementation of the enhanced fireworks algorithm for multi-objective RFID network planning problem,this paperuses hierarchical approach to objectives.It proposes an optimization model of RFID network system that is,to achieve tag100%coverage,to deploy fewer readers,to avoid signal interference while using less transmitting power.For experimentalpurposes it uses standard benchmark sets and makes a comparative analysis withGPSO(Global topology ParticleSwarm Optimization)、VNPSO(Von Neumann topology Particle Swarm Optimization)、GPSO-RNP(Global topologyParticle 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 ofmulti-objectiveRFIDnetwork,and the optimization scheme can be obtained more effectively.

关 键 词：增强烟花算法 无线射频识别 网络规划 优化 

分 类 号：O221.6[理学—运筹学与控制论]