Ant colony optimization (algorithm)

Ant Colony Optimization (ACO) is a problem-solving algorithm inspired by the behavior of real ants. When ants search for food, they leave behind a chemical called pheromone that guides other ants to the food source. ACO mimics this process by using artificial 'ants' to explore paths and leave virtual pheromones based on the quality of solutions they find. Over time, shorter and higher-quality paths are reinforced, while less effective ones fade. This collective behavior helps find optimal solutions to complex problems like route navigation, scheduling, and network design, making ACO a valuable tool in optimization tasks.