What is genetic algorithm?

A genetic algorithm is a search and optimization technique inspired by the process of natural selection. It is used to solve complex problems by mimicking the mechanics of biological evolution. The algorithm starts with an initial set of potential solutions called "individuals" and uses a combination of randomization, mutation, and selection to generate new generations of better solutions over multiple iterations. By evaluating the fitness of each individual, where high fitness represents a better solution, the algorithm gradually converges towards an optimal solution. Genetic algorithms are particularly useful for problems where traditional deterministic approaches are not feasible or too time-consuming, such as combinatorial optimization, scheduling, and machine learning.

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