Ant Colony Optimization — Computational swarm intelligence technique
Anand Nayyar, Rajeshwar Singh · International Conference on Computing for Sustainable Global Development · 2016
Swarm Intelligence being nature inspired intelligence based on collective behavior of swarms having self-organized nature. Various schemes are being formulated in terms of ACO, PSO, Fish Swarm, Bats Swarm, Bacterial Foraging etc. Ant Colony Optimization (ACO) is regarded as high-end computational technique derived by Marco Dorigo in 1999 is based on foraging behavior of real ants. ACO is used to solve various discrete problems in different areas of science and other engineering disciplines. Since its evolution ACO has attracted lots of researchers to take up its algorithms and apply to solve various complex problems and has been proved the best technique to get optimized results. The objective of this research paper is to review Ant Colony Optimization (ACO) — A Computational Swarm Intelligence technique along with its variants and to highlight how this technique is playing a crucial role in solving various Discrete, Stochastic and Dynamic problems.