Simulated
Annealing is a heuristic technique for optimization
problems. Think of an optimization problem as hills and valleys where
you want to find the lowest point. First the ball starts
"hot" and bounces around randomly. As you start to cool the
ball down, it doesn't bounce as much as gravity will cause it to go
down more often than up. When it cools completely it falls into a
local minima. Hopefully you've reduced the temperature at such a rate
that the local minima the ball finds is close to the true minimum.
Simulated annealing doesn't solve NP-complete problems quickly
in general, but it some cases it does reasonably well in practice.
I used an analogy of simulated annealing to describe to a student how
one chooses a research area. First you bounce around for a while
looking at many topics through talks, classes and reading some broad
papers finding the right fit for your strengths and interests. Then
you start to focus, reading more specific papers until you find the
right place to start drilling for results.
One you start drilling you will hopefully find some oil
but eventually the well will just output sludge. At this point you
should start bouncing around again, slowly at first, to find a
new topic. The trick is to know when to start bouncing again. Leave
too early and you might miss a new oil supply right under the old
one. Leave too late and you will find yourself knee-deep in sludge,
forgotten and unable to escape.
Indeed, looking for research topics is pretty much like solving an optimization problem. Although sometimes, it rather looks like an ant algorithm: some ants leave their pheromones on their way to a good food supply, others follow or modify their traces, which usually converges to something close to a shortest path.
And sometimes, the path ends up to be very long and stop in the middle of nowhere...
If we keep up with the oil exploration analogy, I suppose that conference versions are crude oil and the journal refereeing process analogous to the refinement process.