The process of ant colony optimization is a process of very simple rules but very powerful effect in conditions of limited information (as in the case of most of our real problems), and through use of agents that are leaving "traces" of its passage through a specific route.
Can we use this method for the solution of practical problems in everyday life? Indeed, it can be. This approach to a practical problem arises for many years in 1856, and when the designers of Central Park in New York were to define the routes that have crosswalks.
response Robert J. Dillon, one of the designers was that the definition of these roads was postponed until the pedestrians themselves had established the best routes for its use. That is, apovechar proposed swarm intelligence of the people of New York that made use of the park, to determine more efficient routes. Those most used roads would leave alone as marking the pedestrian crossing impedes the growth of vegetation. The
pedestrian crossing and the subsequent delay in the growth of vegetation by this step, equivalent to the pheromone trail left by ants. Furthermore, the subsequent growth of vegetation should not be much pedestrian traffic, equivalent to the evaporation of pheromones, resulting in a nonlinear decrease of trails, paths and deleting non-privileged.
This phenomenon is widely visible in a variety of situations and a variety of sources: 1 .-
busiest roads in the hills for hikers,
2 .- Sites of recommendation from other Internet sites (such as Digg.com , or Stumbleupon, in which case let surfers recommendations of favorite sites, equivalent to "traces" of pheromone viewable by other surfers),
3 .- trail blazed by the Bushmen in the Kalahari Desert,
4 .- Andean Trails used for cattle grazing or migrating, paths in forests used by small mammals,
5 .- etc.
Unfortunately the idea was rejected, but this example of positive feedback has been proven to be a method of obtaining efficient solutions.
"Ant Colony Optimization is a process of very simple rules, But Powerful effect of very limited information in Conditions of (most of Our real problems), and Through the use of agents That leave trails of Their path through to specific route. Could we use
a similar procedure to resolve traveling and networking problems in our own lives? Robert J. Dillon, one of the original Central Park commissioners, had one idea when he suggested in 1856 that the planning of pathways in the park should be postponed until New York City pedestrians had established them by habit, with the more deeply marked paths corresponding to those that were most used and therefore most efficient.
In other words, he proposed making use of the Swarm Intelligence of the population that used Central Park to determine those routes . Those routes used most frequently would become clear as each transit delayed vegetation growth (equivalent to the pheromone trail in the case of an ant colony). On the other hand, if a route was less travelled, vegetation would slowly start to grow again, process that would be equivalent to feromone evaporation, leading to a non-linear elimination of less-privileged routes.
This phenomenon is evident in a series of situations:
1.- Walking trains in mountains, situation similar to the central park example,
2.- Recommendation sites such as Digg.com or StumbleUpon (user recommendation would amount to "pheromone" creation as the recomendation is seen by other users),
3.- Bushmen trails through the kalahari desert,
4.- Trails through forests as used by small animals, etc.
Dillon did not get his way, but recent research by German traffic engineer Dirk Helbing and his colleagues has shown that Dillon’s solution, a neat example of ant colony optimization as Practiced in Humane Society Would Have Been a good one.
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