Linkage Equilibrium and Genetic Algorithms

U.K. Chakraborty; H. Muhlenbein

doi:10.1109/ICEC.1997.592262

Linkage Equilibrium and Genetic Algorithms

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Abstract

The mathematical analysis of recombination/crossover in population genetics and genetic algorithms is very difficult. We investigate a result from H. Geiringer (1944), which states that by repeated applications of the recombination operator alone (with no selective pressure) the gene frequencies of diploid organisms converge to linkage equilibrium. The result is valid for any recombination/crossover scheme. It gives strong support to the conjecture that recombination is not able to explore nonlinear gene interactions. This fact explains the difficulties genetic algorithms have with optimization of fitness functions with nonlinear gene interactions.

Original language	American English
Journal	IEEE International Conference on Evolutionary Computation
DOIs	https://doi.org/10.1109/ICEC.1997.592262
State	Published - Jan 1 1997
Externally published	Yes

Disciplines

Applied Mathematics
Bioinformatics

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10.1109/ICEC.1997.592262License: Unspecified

Cite this

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AB - The mathematical analysis of recombination/crossover in population genetics and genetic algorithms is very difficult. We investigate a result from H. Geiringer (1944), which states that by repeated applications of the recombination operator alone (with no selective pressure) the gene frequencies of diploid organisms converge to linkage equilibrium. The result is valid for any recombination/crossover scheme. It gives strong support to the conjecture that recombination is not able to explore nonlinear gene interactions. This fact explains the difficulties genetic algorithms have with optimization of fitness functions with nonlinear gene interactions.

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Linkage Equilibrium and Genetic Algorithms

Abstract

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