Evolutionary computing: try, select, improve
Some algorithms search for good solutions by imitating the processes of evolution.
How does it work?
The system creates many candidates, scores them, and gradually builds new options from the better ones.
Is this biological evolution?
No. It is a computational analogy based on variation and selection.
Where is it useful?
In optimising designs, planning and tuning parameters.
Does it always find the best solution?
No. It usually looks for a good-enough solution in a huge space of possibilities.
Remember: Being inspired by nature is no proof that a program works like a living thing.
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Last reviewed 1 November 2026. An explainer, not professional, legal or medical advice. For rules and figures that change, check the official version.