Evaluating effectiveness of RFID network planning

Abstract

RFID (Radio Frequency Identification) network planning is the challenge of strategically placing RFID readers in a working area to ensure that each tag can be covered by at least one reader. The objective of the RFID network planning problem is to find the optimal positions of readers so that the network of readers can cover most of the tags while also satisfying certain constraints such as maximum tag coverage, minimum interference, etc. Because the number of potential candidate locations for readers within a working area is typically large, the appropriate solution for this problem is to utilize heuristic methods to find the optimal positions. Various heuristic methods have been proposed, including Artificial Bee Colony (ABC), Cuckoo Search (CS), Firefly Algorithm (FA), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). However, there has been no evaluation and comparison of the effectiveness of these methods in the RFID network planning problem. Therefore, this paper proceeds to compare and evaluate the effectiveness of these heuristic network planning methods. From the simulation results, it can be observed that there is no one-size-fits-all method, and depending on the user's goals and preferences, different heuristic methods can be utilized.