ACO (Ant Colony Optimization) Algorithms

Ant Colony Optimization (ACO) algorithms simulate how real ants find the shortest path to food sources. Ants leave behind a chemical trail called pheromones, which influence other ants to follow successful paths. Over time, the most efficient routes accumulate stronger pheromone signals, guiding future ants to optimal solutions. In computational terms, ACO algorithms use this process to solve complex problems like routing, scheduling, or optimization by iteratively exploring options, reinforcing better solutions, and gradually converging on the best possible outcome. This nature-inspired approach effectively balances exploration and exploitation to find high-quality solutions.