In computer science and operations research, the ant colony optimization algorithm is a probabilistic technique for solving computational problems that can be reduced to finding good paths through gra
Ant behavior was the inspiration for the metaheuristic optimization technique
When a colony of ants is confronted with the choice of reaching their food via two different routes of which one is much shorter than the other, their choice is entirely random. However, those who use the shorter route reach the food faster and therefore go back and forth more often between the anthill and the food.
Loopback vibrators 10×10, synthesized by means of ACO algorithm
Unloopback vibrators 10×10, synthesized by means of ACO algorithm
Swarm intelligence
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Swarm intelligence is the collective behavior of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence. The expression was introduced
Ant colony optimization algorithms
…is more analogous to the foraging patterns of the honey bee, another social insect. This algorithm is a member of the ant colony algorithms family, in swarm intelligence methods, and it constitutes some metaheuristic optimizations. Initially proposed by Marco Dorigo in 1992 in his PhD thesis, the first algorithm was…
A flock of starlings reacting to a predator
Auklet flock Shumagins 1986