A multi-objective meta-heuristic for RFID network planning optimization

Radio Frequency Identification (RFID) technology is increasingly used for tracking and identification purposes. RFID network planning can be considered a difficult optimization problem due to limitations in communications between RFID readers and tags such as short coverage range, power consumption, and interference. This research proposes a multi-objective metaheuristic that maximizes tag coverage and minimizes interference, transmit power consumption, and number of readers in RFID network planning under the constraints of communication distance thresholds, limited number of channels, and transmit power boundaries. In order to allocate tag readers and their assigned frequency channels, unlike existing approaches in the literature, the proposed algorithm considers the dynamic behavior of the network, where wireless propagation, tags movements between readers, and noise existence are included. In addition, the two metaheuristic algorithms, Grey Wolf Optimization (GWO) and Firefly Algorithm (FFA), are compared.