Nature-Inspired Computing: Bat Echolocation to BAT Algorithm

Abstract

The analysis and disclosure of modulation in call structure dynamics of bats in prey catching serves as a raw material for developing engineering modules to solve various kinds of problems. It has always been of interest to biologists to decipher the mechanism of echolocation. There are two groups among these flying mammals old-world fruit bats which do not echolocate and new-world bats which echolocate except a few like Rousettus spp. which is an echolocating fruit bat. The new world fruit bats are smaller in size and are called microbats. They are insectivores and need to catch prey in flight in dark conditions. To perform this task for foraging, they use echolocation. High-pitched sound waves are produced by bats that hit the target and come back to them. These frequency-modulated calls from bats help them in homing their prey. However, the mathematical expression of this mechanism, developed in 2010 by Xin-She Yang is even more interesting. By simply using velocity, frequency, iteration, and loudness, he explained how bats perform homing to catch their prey. The bat echolocation-inspired BAT algorithm is an iconic hallmark of nature-inspired computing. It is a heuristic model for solving problems. New variants have been developed and used for solving problems of diverse nature. In this chapter, we go into the journey of the BAT algorithm, the development of its variants, and the various applications of this algorithm.