New answers tagged genetic-algorithms
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How can you assess the quality of any solution without a measure of quality, which, in the context of genetic algorithms, is known as fitness function? The term fitness function is due to the well-known phrase "Survival of the Fittest", which is often used to describe the Darwinian theory of natural selection (which genetic algorithms are based on)....
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You do not always need an explictly coded fitness function to perform genetic algorithm searches. The more general need is for a selection process that favours individuals that perform better at the core tasks in an environment (i.e. that are "more fit"). One way of assessing performance is to award a numerical score, but other approaches are ...
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You can define different measures in this way:
Maximum distance of the new point with all points of the configuration ($M$)
Minimum distance of the new point with all points of the configuration ($N$)
$\frac{M}{\text{Maximum distance between two points of the configuration(}D)}$: normalize (1) measure
$\frac{N}{D}$:normalize (2) measure
You can get more ...
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