Abstract
The Radio Frequency Identification (RFID) network planning problem is a critical issue because it strongly has an impact on Quality of Service (QoS) and cost efficiency. However, finding an optimal planning for a large scale RFID network is an NP-hard optimization problem. In this context, metaheuristics provides a natural framework to solve this optimization problem by finding a near optimal solution in a reasonable time. In this paper, a new variant of the cuckoo search algorithm, called the Self Adaptive Cuckoo Search (SACS) algorithm, is presented, where control parameters are dynamically adjusted according to the evolution of optimization processes. The SACS algorithm is used to solve real RFID network planning instances. The experimental results show that the proposed algorithm obtains better solutions for the RFID network planning problem than all other adaptive cuckoo search variants in terms of optimization and robustness.
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