Ant colony optimization is a way that ants find the shortest path to food.
Imagine you are an ant and you need to find food. You don't know where it is, but you start wandering around looking for it. As you wander, you leave a trail of pheromones, which are like a perfume that other ants can smell.
Other ants follow your trail, and if they find food, they also leave a trail of pheromones that is stronger than yours. Soon, more and more ants are following the strongest trail of pheromones, which leads directly to the food.
This process is called ant colony optimization. The ants are working together to find the shortest path to food, and they do it by leaving a trail of pheromones that gets stronger the more ants follow it.
In the real world, ant colony optimization is used to solve complex problems. For example, engineers can use it to design better transportation networks or computer scientists can use it to help robots find the fastest way through a maze.
So, just like ants work together to find food, humans can use ant colony optimization to work together and solve problems.