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Download fileImproving genetic algorithms' efficiency using intelligent fitness functions
conference contribution
posted on 2013-08-05, 09:19 authored by Jason CooperJason Cooper, Christopher HindeGenetic Algorithms are an effective way to solve optimisation
problems. If the fitness test takes a long time to perform then the
Genetic Algorithm may take a long time to execute. Using conventional
fitness functions Approximately a third of the time may be spent testing
individuals that have already been tested. Intelligent Fitness Functions
can be applied to improve the efficiency of the Genetic Algorithm by
reducing repeated tests. Three types of Intelligent Fitness Functions are
introduced and compared against a standard fitness function The Intelligent
Fitness Functions are shown to be more efficient.
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