  The Boltzmann model for the random generation of "decomposable" combinatorial
structures is a set of techniques that allows for efficient random sampling
algorithms for a large class of families of discrete objects. The usual
requirement of sampling uniformly from the set of objects of a given size is
somehow relaxed, though uniformity among objects of each size is still ensured.
Generating functions, rather than the enumeration sequences they are based on,
are the crucial ingredient. We give a brief description of the general theory,
as well as a number of newer developments.
