Dear Andrea,
what we do is pretty much what you had guessed already, however there are
two stages of rewriting going on, one for mapping linear expressions into a
linear constraint (that is, a relation between linear expressions) and a
second stage that is done by the functions that post a linear constraint.
Linear expressions are composed as sums and differences of linear terms a*x
+ c. What happens is that this is turned into a linear constraint of the
form (of course, this also holds for <=, >=, !=, <, >). So rather than
creating an expression we create a relation:
a_1 * x_1 + ... + a_n * x_n = c
The routines for posting a linear constraint then do some additional
transformations:
a * x + b * x is rewritten to (a + b) * x [must be
done for better propagation!]
0 * x will be removed
if g is the non-trivial gcd of a_1, ..., a_, c then all coefficients
are devided by g
All these rewriting steps will check for overflow. After that the routines
will decide which precision is needed for propagation and will throw an
exception if propagation might generate an overflow (very important,
otherwise, constraint propagation would be not sound).
I think that's what most systems do and an important aspect is to deal with
relations and not expressions (with expressions you always have the need for
intermediate variables where it is difficult to guess a domain for the
variable so that no overflow occurs). For a discussion of which
transformations change the propagation behaviour, you could check the
following paper:
@Article{newprop-journal,
author = {W.~Harvey and P.J.~Stuckey},
title = {Improving linear constraint propagation by
changing constraint representation},
journal = {Constraints},
volume = {7},
pages = {173--207},
year = {2003},
}
Please do not hesitate to ask if you have more questions.
Cheers
Christian
--
Christian Schulte, www.ict.kth.se/~cschulte/
-----Original Message-----
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf
Of Andrea Rendl
Sent: Monday, August 18, 2008 3:15 PM
To: [EMAIL PROTECTED]; [EMAIL PROTECTED]
Subject: [gecode-users] Linear expressions in 'post'
Dear Gecoders,
I've noticed that Gecode is very effective with solving linear
expressions (Gecode::MiniModel::LinExpr) given in the 'post'
constraint. I was wondering how you deal with them internally. I guess
you build some kind of expression tree from the linear expression and
then map the tree to an adequate 'linear' constraint? How do you deal
with more 'complex' linear expressions that you cannot directly map to
linear, such as
x + c1 != y + c2 (where x,y are IntVars and c1,c2
are constants)
In this case, do you internally re-write the expression to 'x + c1 - y
!= c2' (or similar) to match with linear? If yes, are there any
particular rules you apply for re-writing? I assume there is no case
where you flatten any expressions (and introduce auxiliary variables
internally)? If there exists some published work on it, I'd be happy
if you could point it out to me.
Thank you,
Andrea
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