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To explain simulated annealing to lay audiences, I rely on a similar (inverted) example. You're at the top of the mountain. You want to find the lowest spot. If you just keep walking downhill only, you may reach the sea eventually. But you may never reach Death Valley (86m below sea level) unless you are willing to climb some mountains at the beginning of your trip. IOW you need to accept sub-optimal moves (with decreasing probability) in order to adequately explore your surroundings.


Why not monte carlo your way?


When the solution space is very large Monte Carlo may not get you anywhere useful.




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