Proceedings of the 8th Annual Conference on Genetic and Evolutionary Computation 2006
DOI: 10.1145/1143997.1144210
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Conquering hierarchical difficulty by explicit chunking

Abstract: This paper proposes a chromosome compression scheme which represents subsolutions by the most expressive schemata. The proposed chromosome compression scheme is combined with the dependency structure matrix genetic algorithm and the restricted tournament replacement to create a scalable optimization tool which optimizes problems via hierarchical decomposition. One important feature of the proposed method is that at the end of the run, the problem structure obtained from the proposed method is comprehensible to… Show more

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Cited by 21 publications
(14 citation statements)
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“…Dependency Structure Matrix Genetic Algorithms (DSMGAs) (Yu and Goldberg, 2006), the Extended Compact Genetic Algorithm (ECGA) (Sastry and Goldberg, 2000) and Linkage Identification based on Non-linearity Check (LINC) (Munetomo and Goldberg, 1999) are some of these approaches. All of these and the FGGA can be categorized in the class of genetic algorithms capable of linkage learning.…”
Section: Bh Helmi Et Almentioning
confidence: 99%
See 3 more Smart Citations
“…Dependency Structure Matrix Genetic Algorithms (DSMGAs) (Yu and Goldberg, 2006), the Extended Compact Genetic Algorithm (ECGA) (Sastry and Goldberg, 2000) and Linkage Identification based on Non-linearity Check (LINC) (Munetomo and Goldberg, 1999) are some of these approaches. All of these and the FGGA can be categorized in the class of genetic algorithms capable of linkage learning.…”
Section: Bh Helmi Et Almentioning
confidence: 99%
“…Gámez et al (2008) introduce an approach to approximate multivariate dependency networks by using statistics of order two. The DSMGA (Yu and Goldberg, 2006) is another approach that only uses pair-wise dependencies to find the structure of the fitness function and solve the optimization problem. The original version of the Linkage Tree Genetic Algorithm (LTGA) (Thierens, 2010) uses multivariate statistics, but in the work of Pelikan et al (2011), the algorithm is changed to use only bivariate statistics.…”
Section: Bh Helmi Et Almentioning
confidence: 99%
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“…Several techniques for detecting gene dependency from a population are presented in the literature [14,11]. Similar techniques can also be used to detect the linkage from the states stored in the memory.…”
Section: Linkage Detection and Bb Structure Updatementioning
confidence: 99%