Evolutionary Algorithms
Evolutionary Algorithms (EAs) are a family of optimization algorithms inspired by the process of natural selection. EAs are used to solve complex problems by iteratively improving a population of candidate solutions through the application of genetic operators such as mutation, crossover, and selection. EAs are particularly useful in situations where traditional optimization methods are not effective, such as in high-dimensional search spaces or when the objective function is non-linear, non-convex, or noisy. EAs have been successfully applied in a wide range of fields, including engineering, finance, biology, and computer science.
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