Ordering Genetic Algorithm Genomes With
Reconstructability Analysis
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Stephen Shervais(1) and Martin Zwick(2) |
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(1) College
of Business and Public Administration Eastern
Washington University |
(2)
Systems
Science Ph.D. Program Portland
State University |
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[sshervais@ewu.edu |
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Keywords: Reconstructability
analysis, genetic algorithms, transposition, crossover, optimization, OCCAM
Abstract
The building block hypothesis implies that genetic algorithm effectiveness is influenced by the relative location of epistatic genes on the chromosome. We find that this influence exists, but depends on the generation in which it is measured. Early in the search process it may be more effective to have epistatic genes widely separated. Late in the search process, effectiveness is improved when they are close together. The early search effect is weak but still statistically significant; the late search effect is much stronger and plainly visible. We demonstrate both effects with a set of simple problems, and show that information-theoretic reconstructability analysis can be used to decide on optimal gene ordering.