Uwe Aickelin
A Pyramidal Genetic Algorithm for Multiple-Choice 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. A Pyramidal Genetic Algorithm for Multiple-Choice Problems. Presented at Annual Operational Research Conference 43
Conference Name | Annual Operational Research Conference 43 |
---|---|
Publication Date | Jan 1, 2001 |
Deposit Date | Oct 12, 2007 |
Publicly Available Date | Oct 12, 2007 |
Peer Reviewed | Peer Reviewed |
Public URL | https://nottingham-repository.worktribe.com/output/1023143 |
Files
01or43_partner.pdf
(1.5 Mb)
PDF