Ant Colony Optimization is the limited case of Prim’s Algorithm

Abstract

Swarm intelligence has the capability to recover path with minimum complexity. It only needs small amount of some special purpose information aside from probability information, we can have the value of alpha equal to zero and beta equal to one. So pheromone distribution although is a key feature for discovering minimum path by ants. When I was working on “ACO” I found that changing constraint little bit makes the probabilistic determination of path work only with its component and in this case it is visibility. As its impact is on the distance chosen which can be easily derived as some kind of heuristic such as Manhattan distance or here the distance between two nodes. As there could be case that in case of minimum spanning tree with only single edge originating from a vertex ant gets its final position at the last vertex and in that case from the idea of “aco” we can reach Prim’s but with limitation and that’s why the name that “aco is limited case of Prim’s”. General TermsPheromones, visibility, probability, spanning tree.

Cite this paper

@inproceedings{Raj2012AntCO, title={Ant Colony Optimization is the limited case of Prim’s Algorithm}, author={P. Ananth Raj and Monica Sood}, year={2012} }