Abstract
While the linkage learning genetic algorithm achieved successful genetic linkage learning on problems with badly scaled building blocks, it was less successful on problems consisting of uniformly scaled building blocks. The convergence time model for the linkage learning genetic algorithm developed in the previous chapter explains the difficulty faced by the linkage learning genetic algorithm and reveals the performance limit of the linkage learning genetic algorithm on uniformly scaled problems. This chapter seeks to enhance the design of the linkage learning genetic algorithm based on the time models in order to improve the performance of the linkage learning genetic algorithm.
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Chen, Yp. Introducing Subchromosome Representations. In: Extending the Scalability of Linkage Learning Genetic Algorithms. Studies in Fuzziness and Soft Computing, vol 190. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11339380_8
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DOI: https://doi.org/10.1007/11339380_8
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28459-8
Online ISBN: 978-3-540-32413-3
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