Gene reordering and concurrency in genetic algorithms

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2002

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Şehitoğlu, Onur Tolga

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This study first introduces an order-free chromosome encoding to enhance the performance of genetic algorithms by learning the linkage of building blocks in non-binary encodings. The method introduces a measure called affinity which is based on the statistical properties of gene valuations in the population. It uses the affinity values of the local and global gene pairs to construct a global permutation with tight building block positioning. Method is tested and experimental results are shown for a group of deceptive and real life test problems. Then, study proposes a gene level concurrency model where each gene position is implemented on a different process. This combines the advantages of implicit parallelism and a chromosome structure free approach. It also helps implementation of gene reordering method introduced and probably other non-linear chromosome encodings.

Subject Keywords

Genetic algorithms, Computer algorithms, Algorithms, Concurrency, Reordering, Linkage learning, Deceptive problem

URI

http://etd.lib.metu.edu.tr/upload/12606188/index.pdf
https://hdl.handle.net/11511/12790

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Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

O. T. Şehitoğlu, “Gene reordering and concurrency in genetic algorithms,” Ph.D. - Doctoral Program, Middle East Technical University, 2002.