  Nature-inspired algorithms are commonly used for solving the various
optimization problems. In past few decades, various researchers have proposed a
large number of nature-inspired algorithms. Some of these algorithms have
proved to be very efficient as compared to other classical optimization
methods. A young researcher attempting to undertake or solve a problem using
nature-inspired algorithms is bogged down by a plethora of proposals that exist
today. Not every algorithm is suited for all kinds of problem. Some score over
others. In this paper, an attempt has been made to summarize various leading
research proposals that shall pave way for any new entrant to easily understand
the journey so far. Here, we classify the nature-inspired algorithms as natural
evolution based, swarm intelligence based, biological based, science based and
others. In this survey, widely acknowledged nature-inspired algorithms namely-
ACO, ABC, EAM, FA, FPA, GA, GSA, JAYA, PSO, SFLA, TLBO and WCA, have been
studied. The purpose of this review is to present an exhaustive analysis of
various nature-inspired algorithms based on its source of inspiration, basic
operators, control parameters, features, variants and area of application where
these algorithms have been successfully applied. It shall also assist in
identifying and short listing the methodologies that are best suited for the
problem.
