Borrowed from how metal cools into a strong crystal, simulated annealing wanders freely when hot and settles into the best valley as it cools.
Simulated AnnealingLive
escaping local minima
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Simulated annealing borrows from metallurgy: at high temperature it accepts worse moves freely, letting it jump out of local minima; as it cools, it settles into the best valley it found. The acceptance probability exp(−ΔE/T) is the key. Cool too fast and it gets stuck; cool slowly and it finds the global optimum.
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How it works
Simulated annealing minimizes a rugged objective by accepting worse moves with probability exp(−ΔE/T). At high temperature it roams across the landscape, jumping out of local minima; as the temperature cools, it commits to the best region it found. Cooling too fast traps it early; cooling slowly lets it reach the global optimum — a powerful, general-purpose optimizer.
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