Genetic algorithm (nonfiction): Difference between revisions

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=== Social media ===
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[[Category:Nonfiction (nonfiction)]]
[[Category:Nonfiction (nonfiction)]]


[[Category:Algorithms (nonfiction)]]
[[Category:Genetic algorithms (nonfiction)]]
[[Category:Mathematics (nonfiction)]]
[[Category:Mathematics (nonfiction)]]
[[Category:Ruben bolling (nonfiction)]]

Revision as of 03:48, 8 June 2023

"How to Draw Doug" by Ruben Bolling. This cartoon illustrates the fundamental principles of genetic algorithms.

In the field of mathematical optimization, a genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimization and search problems.

Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection and crossover.

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