Natural Computing Algorithms – A Survey

Abstract

Nature has efficiently provided solutions to complex real world problems since millenniums. This has inspired researchers to develop algorithms based on phenomena in the natural world. Such algorithms are referred as natural computing algorithms. Having the ability to provide optimal solutions to the real world problems, researchers have developed a number of different natural computing algorithms and their variations in the last couple of years. Some of these algorithms are widely known such as Genetic Algorithms, Simulated Annealing, Ant Colony Optimization, Particle Swarm Optimization, Firefly Algorithm, etc. In contrast to these, other algorithms are not known that much such as Fish Swarm Algorithm, Social Cognitive Optimization, Plant Propagation Algorithm, Krill Herd, Grey Wolf Optimizer, etc. This paper attempts to provide readers a comprehensive summary of all the natural computing algorithms developed as early as in the 1970s to the recent ones.

Keywords: Natural Computing Algorithm (NCA), Nature Inspired Algorithm (NIA), Clever Algorithm (CA)