Hi David and Alex,

Thanks for your replies! I'm having trouble communicating it, and the
underspecifiedness doesn't help. Perhaps that just means I don't
really understand the problem. Please let me know if any particular
parts are hazy.

What we *really* care about is getting people to the conference that
otherwise wouldn't. If we have to pick between people with a high
score (say, a speaker who is also a student) and someone with a low
score (someone who doesn't really appear to be very serious about
attending let alone contributing), we'd pick the high scoring person.

When I say score, it's one of the functions in the source file I
linked. Think scalar product; it's a weight vector times ((apply comp
fs) person). I'm flexible as to what that score looks like, but it'd
be nice if there are tweakable values that map directly to real-life
concepts; e.g. I can tell that we're valuing open source contributions
twice as heavily as studenthood.

I'm having trouble conveying more details without having to explain it
in terms of one particular model. Since I've done integer programming
and constraint programming before, I'll do that. Please don't
interpret that as a bias against core.logic and its ilk :-)

Since we're optimizing for attendance weighted by score, we're
minimizing the sum of (* -1 score) of all the people not attending,
subject to the sum of scores of all the people that *are* attending
being less than or equal to the budget.

That actually sounds like something that shouldn't be too hard to dump
into a constraint solver. Perhaps I'll play with Loco tomorrow (it's
late here) and compare the results.

David: does the above clarify somewhat? Would sample data help?

Thanks again!
lvh

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