Dynamic Problems and Nature Inspired Meta-Heuristics

Date of this Version

December 2006

Document Type

Conference Paper

Publication Details

Interim status: Citation only.

Hendtlass, Tim, Moser, Irene and Randall, Marcus (2006) Dynamic Problems and Nature Inspired Meta-Heuristics presented at Second IEEE International Conference on e-Science and Grid Computing (e-Science'06), 4-6 December 2006, Amsterdam.
To obtain a copy of this presentation contact IEEE Computer Society

2006 HERDC submission


Biological systems are, by their very nature, adaptive. However, the meta-heuristic search algorithms inspired by them have mainly been applied to static problems (i.e., problems that do not change while they are being solved). Recently, a greater body of work has been completed on the newer meta-heuristics, particularly ant colony optimisation, particle swarm optimisation and extremal optimisation. This survey paper examines representative works and methodologies of these techniques on this class of problems. Beyond this we outline the limitations of these methods. Copyright © 2007 IEEE Inc. All rights reserved.

This document is currently not available here.



This document has been peer reviewed.