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A class of genetic algorithms with analytical solution

โœ Scribed by Erol Gelenbe

Book ID
104357301
Publisher
Elsevier Science
Year
1997
Tongue
English
Weight
419 KB
Volume
22
Category
Article
ISSN
0921-8890

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โœฆ Synopsis

We study a class of genetic algorithms (GAs) based on a population of chromosomes with mutation and crossover, as well as fitness. The chromosomes in these algorithms also have another property we call "activity" (which determines how fast a chromosome may mutate or interact with other chromosomes). We show how the algorithms we consider can be represented by a multi-dimensional Markov process. We provide a mathematical representation for these GAs, and a closed-form expression for the probability distribution of the number of chromosomes of each type.

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