Genetic algorithm (nonfiction): Difference between revisions

From Gnomon Chronicles
Jump to navigation Jump to search
Line 6: Line 6:


<gallery mode="traditional">
<gallery mode="traditional">
File:Evolved_antenna.jpg|Spacecraft antenna didn't ask to be optimized, would have preferred less efficient but more beautiful design.
File:Evolved_antenna.jpg|Joe's Antenna|[[Joe's Antenna]] didn't ask to be optimized, would have preferred less efficient but more beautiful design.
</gallery>
</gallery>



Revision as of 21:30, 30 August 2016

"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.

In the News

Fiction cross-reference

Nonfiction cross-reference

External links: