This has the advantage of working as a sampling strategy, not just an optimization strategy. It is useful when the mass of your distribution is concentrated in

This has the advantage of working as a sampling strategy, not just an optimization strategy. It is useful when the mass of your distribution is concentrated in a region that may be hard to find with a random walk. https://en.wikipedia.org/wiki/Parallel_tempering https://en.wikipedia.org/wiki/Parallel_tempering Markov-chain Monte-Carlo sampling gives a theoretical underpinning which explains why simulated annealing works in optimization.