If you combine these two models, you get a new model
M3
You should always choose constraints that are of low arity, i.e.
that assignments in one viewpoint can be propagated in the other when
only a few variables have been assigned.
The combination of viewpoints is useless if propagation
via channeling constraints can only occur when a complete assignment
has been made. It can also be an advantage to do a combined model
without constraints that are hard to express in one viewpoint,
provided that the constraints of the other viewpoint together
with the channeling constraints take on their work.
Hence, the advantage of a combined model is the strenghtened
propagation caused by these channeling constraints. If in one
model, say M1
X2
D2
C2
Cc
Channeling constraints
Channeling constraints relate the variables of two
viewpoints. Usually, they are of binary form, i.e.
they relate a single variable in one viewpoint to
a single variable in the other. If an assignment
is made in the model constructed
from one viewpoint, it can be translated into an
assignment in the other and vice versa.