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Old 02-28-2011, 05:32 PM   #1
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Simulated Annealing vs. Stochastic Hill Climbing

Is the only real difference between the two that simulated annealing only allows for neighbors in the correct "temperature" set to be considered while stochastic hill climbing considers everything from the start? Also, if this is the case why does this feature of simulated annealing help prevent getting stuck in a local minimum/maximum?
Old 02-28-2011, 06:15 PM   #2
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Are you trying to compare partial differential equations with Markov processes?
Kevin Barry
Old 02-28-2011, 06:42 PM   #3
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In simulated annealing, the "temperature" acts like a float with a depth probe, while stochastic hill climbing is stuck to the surface.

Actually, stochastic hill climbing is like a runner with severe dementia but sharp wits: not knowing exactly which direction to take, but always downhill. Simulated annealing is like a runner on drugs: tends to run downhill, but will occasionally run uphill too, if high enough.

Last edited by Nominal Animal; 02-28-2011 at 06:55 PM. Reason: Added the runner bit.


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