https://www.hillelwayne.com/tags/minizinc/ Recent content in Minizinc on Hillel Wayne Hugo -- gohugo.io en-us Sun, 30 Sep 2018 00:00:00 +0000 https://www.hillelwayne.com/post/minizinc-2/ Sun, 30 Sep 2018 00:00:00 +0000 https://www.hillelwayne.com/post/minizinc-2/ This is part two of a two-part article. Part one is here. Last time we left off with this model: include "globals.mzn"; enum DAYS; enum ROOMS; enum TIMES; enum talks; constraint assert(card(DAYS) * card(ROOMS) * card(TIMES) == card(talks), "Number of slots must match number of talks"); enum people; array[people, talks] of 0..4: pref; array[DAYS, TIMES, ROOMS] of var talks: sched; constraint alldifferent (d in DAYS, t in TIMES, r in ROOMS) (sched[d, t, r]); array[people] of var int: score; constraint forall(p in people) ( score[p] = sum([if exists (r in ROOMS) (pref[p, sched[d, t, r]] = 4) then 1 else 0 endif | d in DAYS, t in TIMES] ) ); solve maximize sum(score); output ["SCORE: \(sum(score)) \n\n"] ++ [show(sched[d, t, r]) ++ " " ++ if r == card(ROOMS) then if t == card(TIMES) then "\n\n" else "\n" endif else "" endif | d in DAYS, t in TIMES, r in ROOMS]; We wanted to run it for two days, four time slots, and three rooms. https://www.hillelwayne.com/post/minizinc/ Mon, 24 Sep 2018 00:00:00 +0000 https://www.hillelwayne.com/post/minizinc/ This is part one of a two-part article. Part two is here. A while back somebody told me to check out MiniZinc. Eventually I did and really enjoyed it, so figured I’d write about it here. This is actually going to be a two part article. Right now we’re talking about what it is and how it works, and in the next post we’ll talk about optimizing models. MiniZinc is a constraint solving language designed for modeling optimization problems.