MOHAMMEDI, AMIRARAYANE, HAMMMAMOUCHESupervisor: SAYAD, Lamri2022-07-212022-07-212022-06-10https://repository.univ-msila.dz/handle/123456789/30892Radio frequency identification (RFID) technology is a kind of wireless technology that has been successfully employed in various fields, such as object and tracking applications. Nevertheless, one of the main challenges that still remains unsolved in RFID is the network planning(RNP) problem. To overcome this issue, in this work, we proposed a hybrid particle swarm optimization (HPSO) with k-means clustering and virtual forces. Firstly, HPSO-RNP reads automatically the number of readers and then initializes their coordination using the k means algorithm. Lastly, the algorithm (virtual forces) is integrated into the random movement to adjust the location of readers during the search process of PSO. To compare HPSO-RNP with the existing method, extensive experiments are conducted on eight RNP benchmark datasets and the results validate that the performance of the proposed method is superior for planning RFID networks in terms of the number of readers, interference, power and load balance.enparticle swarm optimization ,Radio frequency identification ,RFID network planning , K-means algorithm , Virtual force.Thesis