On the Application of Hierarchical Coevolutionary Genetic Algorithms
Journal of Applied System Sciences, 4(2), pp 2-17, 2003
15 Pages Posted: 17 Aug 2016
Date Written: January 1, 2003
Abstract
This paper examines the use of a hierarchical coevolutionary genetic algorithm under different partnering strategies. Cascading clusters of sub-populations are built from the bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations potentially 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 sub-populations on solution quality are examined for two constrained optimisation problems. We examine a number of recombination partnering strategies in the construction of higher-level individuals and a number of related schemes for evaluating sub-solutions. It is shown that partnering strategies that exploit problemspecific knowledge are superior and can counter inappropriate (sub-) fitness measurements.
Keywords: Genetic Algorithms, Coevolution, Scheduling
Suggested Citation: Suggested Citation