Daniel Dantas

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Taking the ten-city vacation problem from above, we could start at a “high temperature” by picking our starting itinerary entirely at random, plucking one out of the whole space of possible solutions regardless of price. Then we can start to slowly “cool down” our search by rolling a die whenever we are considering a tweak to the city sequence. Taking a superior variation always makes sense, but we would only take inferior ones when the die shows, say, a 2 or more. After a while, we’d cool it further by only taking a higher-price change if the die shows a 3 or greater—then 4, then 5. ...more
Algorithms to Live By: The Computer Science of Human Decisions
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