Session

Mechatronics, Robotics, and System Engineering

Description

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 swarm-based optimisation algorithms and I have presented some examples of real practical applications of these algorithms.

Keywords:

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

Session Chair

Gazmend Bajrami

Session Co-Chair

Kushtrim Dragusha

Proceedings Editor

Edmond Hajrizi

ISBN

978-9951-437-24-0

First Page

152

Last Page

156

Location

Durres, Albania

Start Date

1-11-2013 5:15 PM

End Date

1-11-2013 5:30 PM

DOI

10.33107/ubt-ic.2013.70

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Nov 1st, 5:15 PM Nov 1st, 5:30 PM

Swarm Intelligence as an Optimization Technique

Durres, Albania

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 swarm-based optimisation algorithms and I have presented some examples of real practical applications of these algorithms.