Intro to Scientific Computing
Genetic algorithms are search heuristics that mimic the process of natural selection to solve optimization and search problems. These algorithms use techniques inspired by evolutionary biology, such as selection, crossover, and mutation, to evolve solutions to complex problems over generations. By utilizing random sampling and probabilistic techniques, genetic algorithms effectively explore large search spaces to find optimal or near-optimal solutions.
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