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- W2110346730 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 problem-specific knowledge are superior and can counter inappropriate (sub)fitness measurements." @default.
- W2110346730 created "2016-06-24" @default.
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- W2110346730 date "2008-03-20" @default.
- W2110346730 modified "2023-09-27" @default.
- W2110346730 title "On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners" @default.
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