Jip J. Dekker
fad1b07018
git-subtree-dir: software/minizinc git-subtree-split: 4f10c82056ffcb1041d7ffef29d77a7eef92cf76
116 lines
4.3 KiB
MiniZinc
116 lines
4.3 KiB
MiniZinc
/***
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!Test
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solvers: [gecode]
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expected:
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- !Result
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status: OPTIMAL_SOLUTION
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solution: !Solution
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cost: 48
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s: [4, 1, 2, 3, 6, 5]
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dur: [!!set {2, 4}, !!set {1, 2, 4}, !!set {1, 3, 4}, !!set {1, 3, 4}, !!set {1, 3}, !!set {1, 3}]
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bef: [!!set {}, !!set {2, 4}, !!set {1, 2, 4}, !!set {1, 2, 3, 4}, !!set {1, 2, 3, 4}, !!set {1, 2, 3, 4}]
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aft: [!!set {1, 2, 3, 4}, !!set {1, 2, 3, 4}, !!set {1, 3, 4}, !!set {1, 3, 4}, !!set {1, 3}, !!set {}]
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a: [!!set {1, 2}, !!set {2, 3}, !!set {3, 4}, !!set {2, 4}, !!set {1, 3}, !!set {1, 4}]
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- !Result
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status: OPTIMAL_SOLUTION
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solution: !Solution
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cost: 48
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s: [4, 1, 2, 3, 6, 5]
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dur: [!!set {2, 4}, !!set {1, 2, 4}, !!set {1, 3, 4}, !!set {1, 3, 4}, !!set {1, 3}, !!set {1, 3}]
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bef: [!!set {}, !!set {2, 4}, !!set {1, 2, 4}, !Range 1..4, !Range 1..4, !Range 1..4]
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aft: [!Range 1..4, !Range 1..4, !!set {1, 3, 4}, !!set {1, 3, 4}, !!set {1, 3}, !!set {}]
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a: [!Range 1..2, !Range 2..3, !Range 3..4, !!set {2, 4}, !!set {1, 3}, !!set {1, 4}]
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- !Result
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status: OPTIMAL_SOLUTION
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solution: !Solution
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cost: 48
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s: [5, 3, 2, 1, 4, 6]
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dur: [!!set {1, 3}, !!set {1, 3, 4}, !!set {1, 2, 4}, !!set {1, 2, 4}, !!set {1, 4}, !!set {1, 4}]
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bef: [!!set {}, !!set {1, 3}, !!set {1, 3, 4}, !Range 1..4, !Range 1..4, !Range 1..4]
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aft: [!Range 1..4, !Range 1..4, !!set {1, 2, 4}, !!set {1, 2, 4}, !!set {1, 4}, !!set {}]
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a: [!Range 1..2, !Range 2..3, !Range 3..4, !!set {2, 4}, !!set {1, 3}, !!set {1, 4}]
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- !Result
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status: OPTIMAL_SOLUTION
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solution: !Solution
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cost: 48
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s: [4, 1, 2, 3, 5, 6]
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dur: [!!set {2, 4}, !!set {1, 2, 4}, !!set {1, 3, 4}, !!set {1, 3, 4}, !!set {1, 4}, !!set {1, 4}]
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bef: [!!set {}, !!set {2, 4}, !!set {1, 2, 4}, !Range 1..4, !Range 1..4, !Range 1..4]
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aft: [!Range 1..4, !Range 1..4, !!set {1, 3, 4}, !!set {1, 3, 4}, !!set {1, 4}, !!set {}]
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a: [!Range 1..2, !Range 2..3, !Range 3..4, !!set {2, 4}, !!set {1, 3}, !!set {1, 4}]
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***/
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% mzn2fzn and minizinc aborted on this model with an error message about
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% being unable to compute set bounds. This was fixed in r8782.
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% (This is derived from the talent scheduling model in the MiniZinc
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% benchmarks.)
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include "all_different.mzn";
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int: numActors; % number of actors
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int: numScenes; % numer of scenes
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%-- Types ---------------------------------------------------------------------
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set of int: Actors = 1..numActors;
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set of int: Scenes = 1..numScenes;
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array[Actors,Scenes] of 0..1: ia; % 01 definition of actors in scenes
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array[Scenes] of set of Actors: a :: add_to_output =
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[ { j | j in Actors where ia[j,i] == 1} | i in Scenes] ; % actors for each scene
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array[Scenes] of int: d; % duration of each scene
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array[Actors] of int: c; % cost of each actor
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numScenes = 6;
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numActors = 4;
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ia = [|
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1,0,0,0,1,1|
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1,1,0,1,0,0|
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0,1,1,0,1,0|
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0,0,1,1,0,1|];
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c = [1,1,1,1];
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d = [1,2,3,4,5,6];
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%-- Decision variables --------------------------------------------------------
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array[Scenes] of var Scenes: s :: add_to_output; % schedule of scenes
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%-- Auxilliary variables ------------------------------------------------------
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array[Scenes] of var set of Actors: bef :: add_to_output; % actors appearing before time t
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array[Scenes] of var set of Actors: aft :: add_to_output; % actors appearing after time t
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array[Scenes] of var set of Actors: dur :: add_to_output; % actors on set at time t
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var int: cost :: add_to_output;
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%-- Constraints ---------------------------------------------------------------
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constraint all_different(s); % each scene scheduled once
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constraint
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bef[1] = {} /\ % no actors before time 1
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aft[numScenes] = {} /\ % no actors after time numScenes
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forall(t in 1..numScenes-1)(
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bef[t+1] = a[s[t]] union bef[t] /\
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aft[t] = a[s[t+1]] union aft[t+1] );
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constraint
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dur[1] = a[s[1]] /\
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forall(t in 2..numScenes-1)(
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dur[t] = bef[t+1] intersect aft[t]
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) /\
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dur[numScenes] = a[s[numScenes]];
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constraint cost = sum(i in Scenes)(
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sum(j in Actors)(
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c[j] * d[s[i]] * bool2int(j in dur[i])
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)
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);
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%-- symmetry breaking constraint
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constraint s[1] < s[numScenes];
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%-- Solving objective and solution output -------------------------------------
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solve :: int_search(s, first_fail, indomain, complete)
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minimize cost;
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