Ant Colony Optimization (ACO)and Real Version ACO
Ant Colony Optimization (ACO) and Real Version ACOR
ACOM. Dorigo et al. (1999)Antalgorithms- inspired by the observation of real ant colonies-An important and interesting behavior of antcolonies is their foraging behavior, and, inparticular, how ants can find the shortest pathsbetween food sources and their nest
ACO • M. Dorigo et al. (1999) • Ant algorithms – inspired by the observation of real ant colonies – An important and interesting behavior of ant colonies is their foraging behavior, and, in particular, how ants can find the shortest paths between food sources and their nest
While walkingfromfood sources to thenestand vice versa, ants deposit on the ground asubstance called pheromone, forming in thisway a pheromone trail. Ants can smellpheromone, and when choosing their way,they tend to choose, in probability, pathsmarked by strong pheromone concentrations.The pheromone trail allows the ants to findtheir way back to the food source (or to thenest)
• While walking from food sources to the nest and vice versa, ants deposit on the ground a substance called pheromone, forming in this way a pheromone trail. Ants can smell pheromone, and when choosing their way, they tend to choose, in probability, paths marked by strong pheromone concentrations. The pheromone trail allows the ants to find their way back to the food source (or to the nest)
15cmUpperBranchNestFoodLowerBranch(a)
-%Passagesupperbranch-%Passageslowerbranch10075BREEEEdJE50250051015252030Time (minutes)(b)