The Journal of China Universities of Posts and Telecommunications ›› 2022, Vol. 29 ›› Issue (5): 30-39.doi: 10.19682/j.cnki.1005-8885.2022.0008

Special Issue: Special Topic on Artificial Intelligence of Things

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RFID network planning based on improved brain storm optimization algorithm

Lin Zihan, Zheng Jiali, Xie Xiaode, Feng Minyu, He Siyi   

  • Received:2021-05-11 Revised:2021-12-03 Online:2022-10-31 Published:2022-10-28
  • Contact: Jia-Li ZHENG
  • Supported by:
    National Natural Science Foundation of China;Natural Science Foundation of Guangxi Province, China


In order to improve the service quality of radio frequency identification (RFID) systems, multiple objectives should be comprehensively considered. An improved brain storm optimization algorithm GABSO, which incorporated adaptive learning operator and golden sine operator into the original brain storm optimization (BSO) algorithm, was proposed to solve the problem of RFID network planning (RNP). GABSO algorithm introduces learning operator and golden sine operator to achieve a balance between exploration and development. Based on GABSO algorithm, an optimization model is established to optimize the position of the reader. The GABSO algorithm was tested on the RFID model and dataset, and was compared with other methods. The GABSO algorithm's tag coverage was increased by 9.62% over the Cuckoo search (CS) algorithm, and 7.70% over BSO. The results show that the GABSO algorithm could be successfully applied to solve the problem of RNP.

Key words: radio frequency identification (RFID)| RFID network planning (RNP)| brain storm optimization| golden sine operator

CLC Number: