An obvious probabilistic global search procedure is to use a local algorithm starting from several points distributed over the whole optimization region.
Firstly, they smooth out the likelihood surface, enabling the algorithm to overcome small-scale features of the likelihood during early stages of the global search.
In its basic version the algorithm performs a kind of neighbourhood search combined with global search, and can be used for both combinatorial optimization and continuous optimization.
