Use of Artificial Immune Algorithm with Memory and Suppressor Cells to Optimize the Placement of RFID Portal Reader Antennas

In the past few years, researchers solved the portal reader antennas placement problem to maximize the read accuracy of an RFID portal with an enumeration approach. While the enumeration approach was able to solve the portal reader antenna placement problem, both of the execution time and the CPU computation power consumption are considerable. Therefore, this study attempts to solve the portal reader antennas placement problem with a biology-inspired approach. In this study the method, artificial immune algorithm with memory and suppressor cells method (AIA-MS), are proposed. Experiments were performed to compare the performance among the genetic algorithm method (GA), the CLONALG method and the AIA-MS method. The results showed that, comparing with the execution time and the CPU computation power consumption of the enumeration method, AIA-MS had 97 simulations finding the optimal individuals and only used 30% of the execution time and the CPU computation power consumption in the 100 times simulations. In the same circumstances, CLONALG had 67 simulations and GA only had 26 simulations finding the optimal individuals. AIA-MS thus has the best performance.