This is a very complex issue: in interval analysis we use a lot of
heuristics but it is quite difficult to determine what is the right
combination that will be the most efficient to solve a problem. And
choosing the right parameters for these heuristics may have a very
large influence on the
computation time (and we mean a *really* large with a decrease
factor of the
computation time that may be ).

Usually it is good policy to use filters that may be generated with
simplification procedures (see
section 4.2). For example
the 2B-consistency, see the `Hull_Consistency` procedure,
section 4.2.1) with a
repeat factor that is about the diameter of the initial range
divided by 1000. Similarly it is good policy to use the
3B method (see section 4.5) with an
``ALIAS/Delta3B`` value similar to the factor. You may also
consider looking at the ALIAS-C++ library that provide specific
filters (not all of them are incorporated in ALIAS-Maple) that you may
use to write your own specific simplification procedure.