Critical observation on the exponential growth of nature-inspired computation

We take inspirations from nature very often in solving many complex scientific and day to day problems. Nature inspired computing is a branch of computer engineering deals with the development of algorithms simulating behaviors of natural species for solving complex problems not easily solvable by available computational models. Based on biological systems, various algorithms have been presented in the literature such as Ant Colony Optimization (ACO), Bat Algorithm (BA), Firefly Algorithm (FA), Particle Swarm Optimization (PSO), and many more. The paper critically analyzes the importance and impact of parameter setting for the performance of some of the nature inspired computation, various challenges for them and their application areas.