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Swarm Intelligence
Developed by Dr. Russell Eberhart and Dr. James Kennedy in 1995,
Particle Swarm Optimisation is an Artificial Intelligence technique
based on the study of collective behavior in decentralized,
self-organized systems. Swarm Intelligence is an example of a
“behavior-based” system, as it relies on low-level agents with minimum
competency that are placed in a specific environment and have a limited
time to act. Each agent acts autonomously, without central control, and
the problem-solving nature of the swarm comes from its emergent
behavior. By mimicking the social behavior of bees “swarming” or birds
flocking, this technique represents possible solutions as “particles”
that “swarm” through the search space. Over time, the particles
accelerate towards the “leader,” or the best solution. The main
advantage of Particle Swarm Optimisation over other global optimisation
techniques is the large number of particles that make up the swarm. This
makes the technique notably resilient to the problem of local optima.
To see how SolveIT Software can optimise your operation, please contact us.
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