%0 Journal Article
%A LIN Zi-Han
%A QUAN Yi-Xuan
%A XIE Xiao-De
%A ZHANG Jiang-Bei
%A ZHENG Jia-Li
%T Improved sparrow search algorithm for RFID network planning
%D 2023
%R 10.19682/j.cnki.1005-8885.2023.2010
%J Journal of China Universities of Posts and Telecommunications
%P 93-102
%V 30
%N 1
%X <span>To solve the problem that the performance of the coverage, interference rate, load balance andweak power in the&nbsp;</span><span>radio frequency identification (RFID) network planning. This paper proposes an elite opposition-based learning&nbsp;</span><span>and Levy flight sparrow search algorithm (SSA), which is named elite opposition-based learning and Levy flight&nbsp;</span><span>SSA (ELSSA). First, the algorithm initializes the population by an elite opposed-based learning strategy to&nbsp;</span><span>enhance the diversity of the population. Second, Levy flight is introduced into the scrounger's position update&nbsp;</span><span>formula to solve the situation that the algorithm falls into the local optimal solution. It has a probability that the&nbsp;</span><span>current position is changed by Levy flight. This method can jump out of the local optimal solution. In the end, the&nbsp;</span><span>proposed method is compared with particle swarm optimization (PSO) algorithm, grey wolf optimzer (GWO)&nbsp;</span><span>algorithm and SSA in the multiple simulation tests. The simulated results showed that, under the same number of&nbsp;</span><span>readers, the average fitness of the ELSSA is improved respectively by 3.36%, 5.67% and 18.45%. By setting&nbsp;</span><span>the different number of readers, ELSSA uses fewer readers than other algorithms. The conclusion shows that the&nbsp;</span><span>proposed method can ensure a satisfying coverage by using fewer readers and achieving higher comprehensive&nbsp;</span><span>performance.</span>
%U https://jcupt.bupt.edu.cn/EN/10.19682/j.cnki.1005-8885.2023.2010