A genetic algorithm is a type of optimization algorithm inspired by the natural process of evolution. It is used to solve problems that involve finding the best solution or the optimal values of a set of parameters. The genetic algorithm works by creating a population of individuals (potential solutions), then selecting the fittest individuals based on a fitness function, and breeding them to create a new generation of individuals. This process is repeated, with each generation improving upon the previous one, until the optimal solution is found. The genetic algorithm is used in a variety of applications, including engineering, finance, and biology.
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