Optimal RFID networks planning using a hybrid evolutionary algorithm and swarm intelligence with multi-community population structure

The problem of choosing the optimum locations and the associated parameters of readers in RFID communication systems is considered. All these choices must satisfy a set of objectives, such as tag coverage, load balance, economic efficiency, and interference in order to obtain accurate and reliable network planning. In this paper, a novel optimization algorithm, namely the multi-community GA-PSO, is proposed to solve the complicated RFID network planning problem of large-scale system. The main idea of the algorithm is to divide the single population of the canonical PSO into multi-swarm and use the genetic selection and mutation strategy to improve particle swarm dynamic rules. The simulation results show that the proposed algorithm obtains the superior solution for networking planning problem than canonical PSO does.