Hybridized bat algorithm for multi-objective radio frequency identification (RFID) network planning

This paper introduces implementation of hybridized bat algorithm for multi-objective radio frequency identification network planning problem. Multi-objective RFID problem is a well known hard optimization problem that can be solved by using swarm intelligence algorithms. Bat algorithm is a recent mataheuristic, proved to be very successful for tackling such tasks. In our implementation, we hybridized bat algorithm with the artificial bee colony algorithm and adapted it for solving radio frequency identification network planning problem. In the experimental section, we have first shown, by using standard bound-constrained benchmark functions, that our hybridization is justified and that it improves results compared to standard bat algorithm, as well as to other state-of-the-art algorithms. After that, we examined performance of our proposed approach on illustrative RFID network planning problem and compared it with other results from the literature where our proposed algorithm proved to be more successful.