MITRA ZAREH - Master's student in artificial intelligence ,APADANA university ,Shiraz ,Iran

Ant Colony Optimization (ACO) uses behavior observed in real-life ant colonies in order to solve shortest path problems. Short paths are found with the use of pheromones, which allow ants to communicate indirectly. Ant Colony Optimization (ACO) is a metaheuristic proposed by Marco Dorigo in ۱۹۹۱ based on behavior of biological ants. Pheromone laying and selection of shortest route with the help of pheromone inspired development of first ACO algorithm. Since, presentation of first such algorithm, many researchers have worked and published their research in this field. Though initial results were not so promising but recent developments have made this metaheuristic a significant algorithm in Swarm Intelligence. This research presents a brief overview of recent developments carried out in ACO algorithms in terms of both applications and algorithmic developments.

Multiple traveling salesman problem, Ant Colony Optimization , TSP