ACO (Ant Colony Optimization)

Ant Colony Optimization (ACO) is a nature-inspired algorithm that mimics how ants find the shortest path to food. Ants leave tiny chemical trails called pheromones, which guide other ants to efficient routes. Over time, shorter paths accumulate more pheromones, making them more attractive, while longer ones fade away. In computational problems, ACO uses this behavior to find optimal or near-optimal solutions by simulating virtual "ants" exploring options, updating their trails based on success. It's effective for complex problems like routing, scheduling, and network optimization, leveraging collective behavior to discover efficient solutions.