CIRG - Research  -  Swarm Intelligence 

[Bullet] Home

- NN
- DM
- SI
- EC
- IA
- Bioinf
- Games
- Opt
- FA
- Industry

Contact Us


The Swarm Intelligence focus area is currently the most active in the group, with the largest number of members. The focus area's main interest is particle swarm optimization (PSO), with the development of new and improved PSO algorithms. Theoretical analyses of PSO are also being done, with convergence proofs being studied. Techniques are developed for constrained optimization, niching (locating multiple solutions), multi-objective optimization, dynamic optimization problems, and to cope with discrete search spaces.

Applications of PSO techniques that are under investigation include the coevolutionary training of neural networks for game playing and financial traders, scheduling, image analysis, and data clustering. The research focus area is also investigating the application of ant colony optimization techniques to exploratory data analysis, workload distribution in computer grids, energy efficient routing in mobile ad hoc networks, and network topology design.


List the current members actively doing research in this focus area. [ Show ]


L Schoeman

PhD Completed in 2010

J Grobler

PhD Started in 2009
M.Eng Completed in 2009

S Khan

PhD Completed in 2009

D Barla-Szabo

M.Sc Started in 2003
Hons-B.Sc Completed in 2002

M Neethling

M.Sc Completed in 2008

F Zablocki

M.Sc Completed in 2008

E Papacostantis

M.Sc Started in 2004
Hons-B.Sc Completed in 2003

L Messerschmidt

M.Sc Completed

C Naicker

PhD Started in 2007
M.Sc Completed in 2006
Hons-B.Sc Completed in 2002

J Conradie

Hons-B.Sc Completed in 2004

J du Plessis

M.Sc Completed in 2005

E Peer

M.Sc Completed in 2005

M Omran

PhD Completed in 2005

G Pampara

M.Sc Started in 2005
Hons-B.Sc Completed in 2004

E van Loggerenberg

M.Sc Started in 2005
Hons-B.Sc Completed in 2004

N Franken

PhD Started in 2005
M.Sc Completed in 2004
Hons-B.Sc Completed in 2002

R Brits

M.Sc Completed in 2003
Hons-B.Sc Completed in 2000

U Paquet

M.Sc Completed in 2003

F van den Bergh

PhD Completed in 2002

A Ismail

PhD Started in 2005
M.Sc Completed in 2001


List publications of this research focus area. [ Show ]



 Frans van den Bergh

Portrait photo




 Swarm Intelligence


 Degree specific information: PhD


 An Analysis of Particle Swarm Optimizers


Many scientific, engineering and economic problems involve the optimization of a set of parameters. These problems include examples like minimising the losses in a power grid by finding the optimal configuration of the components, or training a neural network to recognise images of people's faces. Numerous optimisation algorithms have been proposed to solve these problems, with varying degrees of success. The Particle Swarm Optimizer (PSO) is a relatively new technique that has been empirically shown to perform well on many of these optimisation problems. This research develops a theoretical model that can be used to describe the long-term behaviour of the algorithm. An enhanced version of the PSO is constructed and shown to have guaranteed convergence on local minima. This algorithm is extended further, resulting in an algorithm with guaranteed convergence on global minima. A model for constructing cooperative PSO algorithms is also developed, resulting in the introduction of two new PSO-based algorithms. The new PSO models are applied to function optimization tasks and training of product unit neural networks.

 Supervisor / Co-Supervisor:

 AP Engelbrecht



You are visitor #1893
Contact webmaster
Back to top

QualNet Network Simulator University Program Valid XHTML 1.0! Valid CSS!

Computational Intelligence Research Group
University of Pretoria
Copyright © 2018