In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation, crossover and selection.[1] Some examples of GA applications include optimizing decision trees for better performance, solving sudoku puzzles,[2] hyperparameter optimization, causal inference,[3] etc.
https://en.wikipedia.org/wiki/Genetic_algorithm
https://www.boente.eti.br/fuzzy/ebook-fuzzy-mitchell.pdf
