Uwe Aickelin
A pyramidal evolutionary algorithm with different inter-agent partnering strategies for scheduling problems
Aickelin, Uwe
Authors
Abstract
This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the agents on solution quality are examined for two multiple-choice optimisation problems. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.
Citation
Aickelin, U. (2001). A pyramidal evolutionary algorithm with different inter-agent partnering strategies for scheduling problems.
Conference Name | Genetic and Evolutionary Computation Conference 2001, late-breaking papers volume |
---|---|
Conference Location | San Franciso, California, USA |
Start Date | Jul 7, 2001 |
End Date | Jul 11, 2001 |
Publication Date | Jan 1, 2001 |
Deposit Date | Oct 2, 2007 |
Publicly Available Date | Oct 12, 2007 |
Peer Reviewed | Peer Reviewed |
Public URL | https://nottingham-repository.worktribe.com/output/1023127 |
Files
01gecco_partner.pdf
(<nobr>175 Kb</nobr>)
PDF
You might also like
Modelling Reactive and Proactive Behaviour in Simulation: A Case Study in a University Organisation
(2011)
Conference Proceeding
Mimicking the behaviour of idiotypic AIS robot controllers using probabilistic systems
(2009)
Presentation / Conference
Articulation and Clarification of the Dendritic Cell Algorithm
(2006)
Book Chapter
The danger theory and its application to Artificial Immune Systems
(2002)
Conference Proceeding
Genetic algorithms for multiple-choice problems
(1999)
Thesis