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What is fitness function in GA algorithm?

Updated: 12/11/2022
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Nyeinthwet

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15y ago

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In order to understand the fitness function, you first have to understand that a genetic algorithm is one which changes over time (it evolves). In nature we have things like predators and harsh environments which eliminate unwanted specimens of animals (a slow zebra will get eaten by a lion). We need to simulate this behavior when programming genetic algorithms.

The fitness function basically determines which possible solutions get passed on to multiply and mutate into the next generation of solutions. This is usually done by analyzing the "genes," which hold some data about a particular solution to the problem you are trying to solve. The fitness function will look at the genes and make some qualitative assessment, returning a fitness value for that solution. The rest of the genetic algorithm will discard any solutions with a "poor" fitness value and accept any with a "good" fitness value.

In short: the goal of a fitness function is to provide a meaningful, measurable, and comparable value given a set of genes.

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