Ants solve their own version using chemical signals called pheromones. When an ant finds food, she takes it back to the nest, leaving behind a pheromone trail that will attract others. The more ants that follow the trail, the stronger it becomes. The pheromones evaporate quickly, however, so once all the food has been collected, the trail soon goes cold. Moreover, this rapid evaporation means long trails are less attractive than short ones, all else being equal. Pheromones thus amplify the limited intelligence of the individual ants into something more powerful.
Y cómo su racionalización puede hacer más eficientes las redes de distribución reduciendo los trayectos
In 1992 Dr Dorigo and his group began developing Ant Colony Optimisation (ACO), an algorithm that looks for solutions to a problem by simulating a group of ants wandering over an area and laying down pheromones. ACO proved good at solving travelling-salesman-type problems. Since then it has grown into a whole family of algorithms, which have been applied to many practical questions. Its most successful application is in logistics. Migros, a Swiss supermarket chain, and Barilla, Italy’s leading pasta-maker, both manage their daily deliveries from central warehouse to local retailers using AntRoute. This is a piece of software developed by AntOptima, a spin-off from the Dalle Molle Institute for Artificial Intelligence in Lugano (IDSIA), one of Europe’s leading centres for swarm intelligence. Every morning, the software’s “ants” calculate the best routes and delivery sequences, depending on the quantity of cargo, its destinations, delivery windows and available lorries. According to Luca Gambardella, the director of both ISDIA and AntOptima, it takes 15 minutes to produce a delivery plan for 1,200 trucks, even though the plan changes almost every day.
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