Ant colony optimization in dynamic environments

A comparison of six basic Ant Colony Optimization (ACO) in dynamic environment was studied in this paper. Dynamic Traveling Salesman Problem (TSP) will be used as a dynamic environment. A number of cities are swap over time to make the TSP environment dynamic. A pheromone equalization strategy was applied in all the six ACO to react to the change. Three sets of TSP are used in this experiment. The result will show which of the six basic ant algorithms work best in dynamic environment