Introducing Subchromosome Representations to the Linkage Learning Genetic Algorithms

Abstract:
This paper introduces subchromosome representations to the linkage learning
genetic algorithm (LLGA). The subchromosome representation is utilized for effectively lowering the number of building blocks in order to escape from
the performance limit implied by the convergence time model for the linkage
learning genetic algorithm. A preliminary implementation to realize
subchromosome representations is developed and tested. The experimental
results indicate that the proposed representation can improve the
performance of the linkage learning genetic algorithm on uniformly scaled
problems, and the initial implementation provides a potential way for the
linkage learning genetic algorithm to incorporate prior linkage information
when such knowledge exists.

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