计算机科学

计算机科学 ›› 2021, Vol. 48 ›› Issue (9): 292-297.doi: 10.11896/jsjkx.200700167

• 计算机网络 • 上一篇    下一篇

基于改进型多目标樽海鞘群算法的RFID阅读器天线优化部署

罗文聪, 郑嘉利, 全艺璇, 谢孝德, 林子涵   

  1. 广西大学计算机与电子信息学院 南宁53000
    4广西多媒体通信与网络技术重点实验室 南宁530004
  • 收稿日期:2020-07-26 修回日期:2020-09-25 出版日期:2021-09-15 发布日期:2021-09-10
  • 通讯作者: 郑嘉利(zjl@gxu.edu.cn)
  • 作者简介:1813391010@st.gxu.edu.cn
  • 基金资助:
    国家自然科学基金(61761004);广西自然科学基金(2019GXNSFAA245045)

Optimized Deployment of RFID Reader Antenna Based on Improved Multi-objective Salp Swarm Algorithm

LUO Wen-cong, ZHENG Jia-li, QUAN Yi-xuan, XIE Xiao-de, LIN Zi-han   

  1. School of Computer,Electrionics and Information,Guangxi University,Nanning 530004,ChinaGuangxi Key Laboratory of Multimedia Communications and Network Technology,Nanning 530004,China
  • Received:2020-07-26 Revised:2020-09-25 Online:2021-09-15 Published:2021-09-10
  • About author:LUO Wen-cong,born in 1996,postgra-duate.His main research interests include RFID and swarm intelligence.
    ZHENG Jia-li,born in 1979,Ph.D,professor,is a member of China Computer Federation.His main research interests include Internet of things,RFID and artificial intelligence.
  • Supported by:
    National Natural Science Foundation of China(61761004) and Natural Science Foundation of Guangxi Province,China(2019GXNSFAA245045)

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摘要： 随着射频识别(Radio Frequency Identification,RFID)技术的飞速发展,在各种特殊的环境下(如工厂、仓库、监狱等),对RFID阅读器天线优化部署的需求开始受到广泛关注。针对目前RFID阅读器天线部署中存在的部署难度大、约束条件多且不易找到最优解和Pareto前沿等问题,文中提出了一种基于改进型多目标樽海鞘群算法(Multi-objective Salp Swarm Algorithm,MSSA)的RFID阅读器天线优化部署方法。预先构建多目标RFID阅读器天线优化部署模型,设定优化目标;多目标樽海鞘群算法对RFID阅读器天线优化部署模型进行优化训练,引入分离算子以优化搜索能力,并通过迭代不断寻找满足条件的非支配解,构建满足条件的Pareto解集,其即为优化的结果。实验数据表明,MSSA算法求解时无需先验知识和设置加权系数,收敛速度快;在相同实验环境下,MSSA算法与带观察者机制的蝙蝠(BA-OM)算法、粒子群(PSO)算法、细菌觅食优化(MC-BFO)算法相比,覆盖率分别提高了33%,28%,20%;与同类型的求Pareto解集的混合萤火虫(HMOFA)算法相比,MSSA算法的负载均衡提高了7.14%,经济效益提高了59.74%,阅读器干扰减少34.04%。

关键词: Pareto解集, RFID, 多目标樽海鞘群算法, 分离算子, 优化部署

Abstract: ith the rapid development of radio frequency identification (RFID) technology,in a variety of special environments (such as factories,warehouses,prisons,etc.),the demand for optimal deployment of RFID reader antennas has attracted extensive attention.In order to solve the problems in the deployment of RFID reader antenna,such as difficult deployment,many constraints and difficult to find the optimal solution and Pareto front,this paper proposes an optimized deployment method of RFID reader antenna based on the improved multi-objective SALP swarm algorithm (MSSA).The multi-objective optimization deployment model of RFID reader antenna is constructed in advance,and the optimization target is set.The multi-objective tympana algorithm is used to train the optimal deployment model of RFID reader antenna.The separation operator is introduced to optimize the search ability,and the non dominated solutions satisfying the conditions are searched continuously through iteration,and the Pareto solution set satisfying the conditions is constructed,which is the optimization result.The results show that the proposed algorithm has faster convergence rate than the algorithms of BA-OM,PSO and MC-BFO without the prior knowledge,coverage rate increases by 33%,28% and 20% respectively.Compared with the same type of hybrid firefly (HMOFA) algorithm for Pareto solution set,the load balancing is increased by 7.14%,the economic benefit is increased by 59.74%,and the reader interfe-rence is reduced by 34.04%.

Key words: Multi-objective salp swarm algorithm, Optimal deployment, Pareto set, RFID, Seperating operator

中图分类号: 

  • TP301.6
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