On 06-06-13 10:22, Michiel Vermandel
The business analysis defines the score weights, it's not our call
to make which is more important etc.
I'm struggling with
assigning weights to IntConstraintOccurrence in a rule's
If I assign different
weights for different rules (because we think one rule is
more important than an other)
One way talk to you your business people and get them to convert
their knowledge into score weights
is to ask "if you had to put a price tag on everything, how much
would violating this constraint cost us?".
Basically normalize everything to a price.
For example: in nurse rostering, "not giving a nurse her day off
requests costs the solution 100 $".
It might seem unethical to put a price tag on a nurse's happiness,
but reality does it implicitly anyway.
That's comparing apples and oranges.
our end result is far
worse than when we assign all equal weights.
I do not look at the
total value of hard and soft score but at the number of
If you have 2 solutions A and B scored using a different score
function, it's impossible to state whether A is better/worse than B
based on those scores or the number of violations.
What you can do is take solution B and grind it through A's score
function to compare it with score A (or vica versa).
Yes, if and only if the more difficult constraints have higher
weights (otherwise it's the opposite).
I can imagine that the
planner can evolve much easier to a better solution with all
weights being the same because if not then "transient" moves
will be made impossible to take.
But it's a bit absurd. For example in nurse rostering, I could give
all nurses their day off requests if I didn't have to worry about
assigning no more than 2 shifts to the same nurse as the same
Define your score function as your business needs it. Use the
techniques described in the 6.0 manual: negative/postive, weights
But how should we then
implement importance in rules?
PS: 6.0.0.Beta3 is out and the new addSoftConstraintMatch() system
is much faster and easier to use (see the blog post of a few months
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