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- Title
Improved multi-objective brain storm optimization algorithm for RFID network planning.
- Authors
Zheng, Jiali; Lin, Zihan; Xie, Xiaode
- Abstract
The problem of radio frequency identification network planning (RNP) is one of the biggest challenges in the field of RFID research. In order to improve the service quality of RFID systems, in addition to finding the optimal number and location of readers, the interference between readers and tag coverage should be considered. In order to solve the problem of RFID network planning, this paper proposes an improved multi-objective brainstorming optimization algorithm (IMBSO) based on decomposition: Employ the golden sine operator to improve the convergence speed of the algorithm, and the Cauchy mutation operator is introduced to enhance the ability of the algorithm to jump out of the local optimum. The improved algorithm achieves a balance between exploration and development. This paper also combines the decomposition-based method with the IMBSO algorithm to establish an optimization model to optimize the reader position: the multi-objective optimization problem is transformed into multiple sub-problems by means of decomposition, all objective functions are optimized at the same time, which improves the search efficiency. The method proposed in this paper was tested on the RFID model and data set. Under the same experimental conditions, it was compared with multi-objective particle swarm optimization algorithm, multi-objective firefly algorithm and multi-objective brainstorming algorithm. The experimental results show that the algorithm proposed in this paper can be successfully applied to the problem of radio frequency identification network planning by achieving smaller interference and fewer readers while ensuring greater coverage.
- Subjects
OPTIMIZATION algorithms; PARTICLE swarm optimization; RADIO frequency identification systems; BRAINSTORMING; HUMAN fingerprints
- Publication
Wireless Networks (10220038), 2024, Vol 30, Issue 2, p1055
- ISSN
1022-0038
- Publication type
Article
- DOI
10.1007/s11276-023-03543-x