Communications of the ACM
What Complex Technology Can Learn From Simple Ants
Ants' pheromone-laying and -following behavior has inspired an optimization algorithm.
Credit: The Boston Globe
Ants' pheromone-laying and -following behavior has inspired an optimization algorithm.
Conceived by Marco Dorigo at the Free University of Brussels in Belgium, the algorithm uses artificial ants in a virtual environment to solve optimization problems; pheromones deposited by the ants are actually numeric values, and this sequence of artificial pheromone values is called an artificial pheromone trail.
Artificial ants move through each step of an assigned problem, making probabilistic decisions based on pheromone concentrations.
Dorigo's algorithm has been used with real-world vehicle routing problems for delivery and distribution, along with scheduling optimization problems.
For example, Southwest Airlines modeled the foraging behavior of ants and applied that to its cargo routing and handling system, resulting in an 80% decrease in freight transfer rates and a 20% reduction in the workload of cargo handlers. The airline also has used ant behavior as a platform for determining efficient ways of boarding a plane, and to assigning airplane arrivals to airport gates.
From The Boston Globe
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