Evolutionary Algorithms (EAs) are a class of optimization algorithms inspired by biological evolution. They use mechanisms like selection, mutation, and crossover to iteratively improve a population of candidate solutions to a problem. They are commonly used for solving complex optimization problems where traditional methods may be ineffective, such as in machine learning, engineering design, and operations research.
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