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Keywords

Optimization, swarm Intelligence, Ant Colony Optimization, Particle Swarm Optimization, Artificial Bees Colony

Abstract

Optimization techniques inspired by swarm intelligence have become increasingly popular during the last years. Swarm intelligence is based on nature-inspired behaviours and is successfully applied to optimisation problems in a variety of fields. The advantage of these approaches over traditional techniques is their robustness and flexibility. These properties make swarm intelligence a successful design paradigm for algorithms that deal with increasingly complex problems. In this paper I am focused on the comparison between different swarmbased optimisation algorithms and I have presented some examples of real practical applications of these algorithms.

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