•  
  •  
 

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.

DOI

10.33107/ijbte.2014.2.2.01

First Page

2

Last Page

5

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.