A Novel Bat Algorithm as ‘Range Determination’

Background: Bat Algorithm is one of the swarm intelligence techniques inspired from the echolocation of bats. In this work, many variants of Bat Algorithm are studied which are developed by various researchers. Despite its drawback of getting trapped in local optima, it is preferred over other swarm intelligence techniques. Considering the performance of Bat Algorithm and to extend the existing work, biological behavior of bats is explored in this research work. Objective: One of the characteristics of real bats, i.e. range determination, was adopted to propose a new variant of Bat Algorithm. Methods: The proposed algorithm computed “distance” using cross correlation of emitted pulse and received echo. Results: The performance of Range Determiner-Bat Algorithm (RD-Bat Algorithm) was compared with Standard Bat Algorithm on the basis of best, median, mean, worst and standard deviation values. Conclusion: Experimental results of proposed algorithm outperformed the standard Bat Algorithm.