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CORR
2008
Springer

Partnering Strategies for Fitness Evaluation in a Pyramidal Evolutionary Algorithm

13 years 11 months ago
Partnering Strategies for Fitness Evaluation in a Pyramidal Evolutionary Algorithm
This paper combines the idea of a hierarchical distributed genetic algorithm with different interagent 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 subpopulations search a larger search space with a lower resolution whilst lower-level subpopulations search a smaller search space with a higher resolution. The effects of different partner selection schemes for (sub-)fitness evaluation purposes are examined for two multiple-choice optimisation problems. It is shown that random partnering strategies perform best by providing better sampling and more diversity.
Uwe Aickelin, Larry Bull
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2008
Where CORR
Authors Uwe Aickelin, Larry Bull
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