Dear Raphael,
thank you so much! Your solution is exactly what I needed!!
This "propagator" is very useful for computing segmentations of a given
length N (e.g. 5):
5
4 1
3 2
3 1 1
2 3
2 2 1
2 1 2
2 1 1 1
1 4
1 3 1
1 2 2
1 2 1 1
1 1 3
1 1 2 1
1 1 1 2
1 1 1 1 1
The real model in Oz would be:
5 0 0 0 0
4 1 0 0 0
3 2 0 0 0
3 1 1 0 0
2 3 0 0 0
2 2 1 0 0
2 1 2 0 0
2 1 1 1 0
1 4 0 0 0
1 3 1 0 0
1 2 2 0 0
1 2 1 1 0
1 1 3 0 0
1 1 2 1 0
1 1 1 2 0
1 1 1 1 1
When I have another sequence of same length that represents the
"partial sums" from left until each point, I need your propagator to
make it increasing until the goal is reached and thus allowing
zeroes, but only at the end (this is related to a problem of Torsten
Anders).
Just imposing {FD.sum MySequence '=:' 5} as I did in the beginning,
does not propagate very well as soon as the domains contain zeroes.
Now, your propagator allows me to get /maximum propagation/ [1] !!! :)
Many thanks again,
Kilian
[1] About maximum propagation: I just discovered for myself this
probably very well known concept....what I enjoy about it that it is
perfectly possible to define it (empirically) by analyzing an all
solution search... By comparing this with a propagator to be tested
you can see exactly what you are missing and your help leads me to
100% propagation !
I am wondering whether you pros are using this kind of strategy of
unit testing when developing new propagators?
Am 04.04.2007 um 09:28 schrieb Raphael Collet:
Dear Kilian,
I scratched my head quite a bit yesterday, and I just found a nice
solution to your problem. The idea is to avoid reification,
because propagation is too poor in that case.
Kilian Sprotte wrote:
I am looking for a way to constrain a sequence to be "ascending
towards a goal". The goal is determined before posting, let's say
its 5, so a solution could be:
[1 2 4 5 5]
Let us call this sequence S. It can be defined as:
declare
Goal=5
N=5
S={FD.list N 1#Goal}
The issue is that S is strictly increasing, except when values
reach the goal. My idea is to combine the propagators <: and
FD.min. Consider another sequence, say T, that is strictly
increasing, and where values may be greater than the goal:
declare
T={FD.list N 1#(Goal+N-1)}
for A in T B in T.2 do A <: B end % strictly increasing
The link with S is done by taking the minimum between the Goal and
each element of T:
for X in S Y in T do X={FD.min Goal Y} end
Both propagators <: and FD.min will propagate of the variables'
domains, and propagates exactly as you wanted:
[1#5 2#5 3#5 4#5 5]
Try to constrain the 3rd element of S to value 4 in the example,
and you will see that the 4th element is constrained to 5.
Cheers,
raph
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