A Comparative study on Ant Colony Optimization

Ant Colony optimization is a computational method which can be used for finding best solutions and the paths for best solutions.Ant Colony Optimization (ACO) is a derivative of Swarm intelligence (SI). It is based on the criterion which the real ants follow. As the ants move in search of food followed by other ants, similarly, the artificial ants are made to move on a weighted graph. Actually the model ants undergo the movement along with some parameters in their routes, dropping pheromones and indicating the following ants. Introduced by Marco Dorigo in the year 1992, ant colony algorithm is having a variety of applications in the field of artificial intelligence.This paper discusses ACO algorithm, improved ant colony optimization algorithm, recent researches in engineering domain and its applications.